CN118869061A - An all-optical routing intelligent communication switching protection method based on MEMS technology - Google Patents

Abstract

The invention relates to the field of digital information transmission, in particular to an all-optical-path routing intelligent communication switching protection method based on MEMS technology. The method comprises the steps that optical signal data acquisition processing is carried out on all-optical routes through an MEMS sensor, so that node optical signal data are obtained; carrying out communication frequency analysis on the node optical signal data to obtain a communication frequency chart; performing peak spectrum bandwidth coverage analysis and abnormal influence communication evaluation analysis on the node optical signal data to obtain spectrum abnormal communication influence data; performing reflection curve construction processing on the light pulse time characteristic data to obtain a light signal reflection curve; performing abnormal influence communication evaluation analysis on the optical signal reflection curve based on the optical signal spectrogram to obtain optical signal reflection abnormal communication influence data; carrying out abnormal communication strategy analysis on the communication frequency chart based on the two communication influence data to obtain an abnormal channel switching strategy; the invention optimizes the abnormal data analysis and ensures the optimization of the communication switching speed.

Description

An all-optical routing intelligent communication switching protection method based on MEMS technology

Technical Field

The invention relates to the field of digital information transmission, and in particular to an all-optical routing intelligent communication switching protection method based on MEMS technology.

Background Art

Traditional optical communication networks rely on electronic switching nodes for routing and managing optical signals, which become performance bottlenecks, limiting system speed and increasing latency. MEMS technology is used in optical communication networks for efficient and flexible traffic management and fault protection information transmission. MEMS is a micro-electromechanical system technology that combines micron-scale electronic and mechanical components to achieve miniaturized, high-performance devices. In the field of optical communications, MEMS technology can achieve precise control and regulation of optical paths, realize direct transmission and switching of optical signals for all-optical routing, avoid the photoelectric conversion process, and improve network transmission efficiency and bandwidth utilization. However, MEMS technology is a micro-electromechanical system technology. In terms of communication switching, there is a limitation that the mechanical movement of MEMS technology for analyzing optical signal anomalies is relatively slow compared to the speed of optical signals.

Summary of the invention

Based on this, it is necessary for the present invention to provide an all-optical routing intelligent communication switching protection method based on MEMS technology to solve at least one of the above technical problems.

An all-optical routing intelligent communication switching protection method based on MEMS technology comprises the following steps:

Step S1: performing optical signal data acquisition and processing on the all-optical routing through a MEMS sensor to obtain node optical signal data; performing optical pulse characteristics and spectrum analysis on the node optical signal data to obtain optical pulse time characteristic data and an optical signal spectrum diagram; performing communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram;

Step S2: Based on the node optical signal data, a peak analysis is performed on the optical signal spectrum to obtain wavelength spectrum peak data; a spectrum bandwidth coverage analysis is performed on the optical signal spectrum to obtain optical signal coverage frequency range data; based on the wavelength spectrum peak data and the optical signal coverage frequency range data, an abnormal impact communication evaluation analysis is performed on the optical signal spectrum to obtain spectrum abnormality communication impact data;

Step S3: constructing a time domain waveform for the optical pulse time characteristic data to obtain an optical time domain waveform; constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve; and evaluating and analyzing the abnormal impact of the optical signal reflection curve on communication based on the optical signal spectrum to obtain optical signal reflection abnormality communication impact data;

Step S4: Based on the spectral abnormal communication impact data and the optical signal reflection abnormal communication impact data, the communication frequency map is subjected to image fitting processing to obtain a spectral reflection frequency map; the spectral reflection frequency map is subjected to spectral reflection anomaly fusion index analysis to obtain a spectral reflection anomaly fusion index; based on the spectral reflection anomaly fusion index and the all-optical routing node data, an abnormal communication strategy analysis is performed on the all-optical routing to obtain an abnormal channel switching processing strategy.

The present invention uses MEMS sensors to obtain optical signal data in all-optical routing and conducts a comprehensive analysis of the optical performance of the node. Optical pulse characteristics and spectral analysis provide valuable insights into the time and frequency characteristics of optical signals. Communication frequency analysis is performed on the time characteristics and spectral diagram of optical pulses to reveal any potential interference or conflict. Spectral peak analysis is performed on the node optical signal data to identify specific wavelengths in the optical signal, which helps to understand any potential wavelength-related anomalies. Spectral bandwidth coverage analysis provides the frequency range covered by the optical signal, which is very important for evaluating communication quality and potential frequency interference. Spectral peak and coverage data are combined to evaluate the impact of optical anomalies on communication. An optical time domain waveform is constructed to represent the change of the optical signal over time, which helps to detect any time-related characteristics or anomalies. The reflection curve construction based on the optical time domain waveform provides insights into the reflection characteristics of the optical signal. It is very useful for understanding network performance and identifying any interference caused by reflection. The optical signal reflection curve is combined with the spectrum diagram to evaluate the impact of reflection anomalies on communication. The spectral reflection frequency diagram is generated by image fitting processing of the communication frequency diagram, which provides a frequency domain representation of the optical signal reflection characteristics and reveals the relationship between reflection and frequency. Based on the spectral reflection frequency diagram, the spectral reflection anomaly is analyzed by fusion index to obtain the spectral reflection anomaly fusion index. The index quantifies the degree of influence of the reflection anomaly in the entire frequency range, which is beneficial to the final intelligent switching of all-optical routing. Finally, by considering the spectral reflection anomaly fusion index and all-optical routing node data, the abnormal communication strategy is analyzed and the channel switching processing strategy is formulated, which is beneficial to optimize the operation of EMES technology in the process of switching channel protection, and optimizes the optical signal abnormal operation speed to reduce the impact of mechanical components on switching channels in order to optimize the signal processing strategy.

Preferably, step S1 comprises the following steps:

Step S11: performing communication node identification processing on the all-optical routing to obtain an all-optical routing node;

Step S12: performing optical signal data acquisition processing on the all-optical routing node through the MEMS sensor to obtain the node optical signal data;

Step S13: performing optical pulse time characteristic analysis on the node optical signal data to obtain optical pulse time characteristic data;

Step S14: performing spectrum analysis on the node optical signal data to obtain an optical signal spectrum graph;

Step S15: Perform communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram.

The present invention performs communication node identification processing on the all-optical routing to determine the position and identity of each node, provides accurate node information for subsequent data collection and analysis, and is beneficial to system management and monitoring; uses MEMS sensors to obtain and process optical signal data of the all-optical routing nodes, monitors the optical signal conditions of the nodes in real time, and provides a data basis for subsequent optical signal analysis and abnormal processing; performs optical pulse time feature analysis on the optical signal data of the nodes to extract the time feature data of the optical signals, which is helpful to understand the transmission speed and time characteristics of the optical signals and provides an important reference for communication frequency analysis; performs spectrum analysis on the optical signal data of the nodes to obtain the spectrum features of the optical signals, which is helpful to understand the frequency distribution of the optical signals and provides a basis for communication frequency analysis and system optimization; performs communication frequency analysis on the optical signal data of the nodes by combining the optical pulse time feature data with the optical signal spectrum; is beneficial to revealing the communication frequency patterns used in the network, and helps detect potential frequency conflicts, interferences or unused frequency bands by identifying and analyzing these frequency patterns, thereby optimizing optical communication performance and ensuring efficient spectrum utilization.

Preferably, step S15 comprises the following steps:

Step S151: performing optical phase analysis on the optical pulse time characteristic data to obtain an optical pulse phase spectrum;

Step S152: performing optical pulse repetition frequency analysis on the optical pulse phase spectrum to obtain the optical pulse repetition frequency;

Step S153: performing frequency analysis on the optical signal spectrum to obtain the optical signal spectrum frequency;

Step S154: performing communication frequency analysis on the node optical signal data based on the optical pulse repetition frequency and the optical signal spectrum frequency to obtain optical signal communication frequency data;

Step S155: Perform frequency mapping processing on the optical signal communication frequency data to obtain an optical signal communication frequency map.

The present invention performs optical phase analysis on the optical pulse time characteristic data to obtain the phase spectrum of the optical pulse and reveal the phase characteristics of the optical signal, which helps to understand the phase change of the optical pulse and detect the potential existence of phase encoding or phase modulation, providing a basis for subsequent frequency analysis; by analyzing the optical pulse phase spectrum, the repetition frequency of the optical pulse is determined to help identify the pulse characteristics of the light source and reveal the specific pulse mode used by the optical communication system. Determining the repetition frequency of the optical pulse is crucial for subsequent signal processing and analysis; performing frequency analysis on the optical signal spectrum diagram can reveal the spectrum distribution of the optical signal, by identifying the peaks in the spectrum, these peaks represent the optical communication channel and the specific frequency components that exist, and by analyzing Analyze the optical signal spectrum frequency to obtain important insights about the interference in the transmission signal or channel; integrate the optical pulse repetition frequency and optical signal spectrum frequency information to perform a comprehensive communication frequency analysis on the node optical signal data, which helps to identify the actual communication frequency used in the optical signal and reveal the frequency conversion technology. Through this frequency analysis, we can better understand the optical communication system and its operating parameters; by frequency mapping the optical signal communication frequency data to obtain an intuitive optical signal communication frequency map, it is helpful to quickly identify the communication frequency mode, frequency band usage or any potential interference in the system. The communication frequency map can provide valuable information for the design and optimization of optical communication systems, as well as the formulation of spectrum utilization and interference management strategies.

Preferably, step S2 comprises the following steps:

Step S21: dividing the node optical signal data by wavelength characteristics to obtain optical signal wavelength characteristic data;

Step S22: Analyze the optical signal spectrum based on the optical signal wavelength characteristic data to obtain a wavelength characteristic spectrum;

Step S23: performing peak analysis on the wavelength characteristic spectrum to obtain wavelength spectrum peak data;

Step S24: performing spectrum bandwidth coverage analysis on the optical signal spectrum diagram to obtain frequency range data covered by the optical signal;

Step S25: performing a spectrum abnormality analysis on the optical signal spectrum based on the wavelength spectrum peak data and the optical signal coverage frequency range data to obtain optical signal abnormal spectrum data;

Step S26: performing abnormal impact analysis on the optical signal abnormal spectrum data to obtain abnormal spectrum communication impact data.

The present invention divides the wavelength characteristics of the node optical signal data and accurately extracts the key information about the wavelength of the optical signal, which provides important support for determining the different wavelengths used in the optical communication system. The acquisition of wavelength characteristic data is crucial for in-depth understanding of the characteristics of the optical signal and the wavelength-related effects in the optical channel, which is helpful for system design and performance optimization. Based on the wavelength characteristic data of the optical signal, the spectrum analysis is performed to obtain the wavelength characteristic spectrum diagram, which can accurately describe the spectrum characteristics of the optical signal at different wavelengths and provide key clues for further analysis. By performing peak analysis on the wavelength characteristic spectrum diagram and obtaining the wavelength spectrum peak data, the peak characteristics in the spectrum can be accurately identified, providing an important reference for abnormal analysis and signal optimization; the spectrum bandwidth coverage analysis can determine the entire frequency range covered by the optical signal, which helps to make full use of spectrum resources and discover the existence of different channels and frequency ranges; by understanding the frequency range covered by the optical signal in detail, it can provide important data for the evaluation of the system bandwidth requirements, optimize communication performance, and improve system stability and efficiency. These comprehensive analysis steps help to fully understand the wavelength characteristics and frequency distribution of the optical signal, provide key support for the design and optimization of the optical communication system, further improve the reliability and performance of the communication system, and promote the development of optical communication technology.

Preferably, step S25 comprises the following steps:

Step S251: performing main wavelength identification processing on the optical signal spectrum diagram based on the wavelength spectrum peak data to obtain main wavelength data of the spectrum;

Step S252: performing abnormal side peak analysis on the optical signal spectrum based on the main wavelength data of the spectrum to obtain abnormal side peak data;

Step S253: performing abnormal noise spectrum bandwidth analysis on the optical signal spectrum to obtain noise coverage frequency range data;

Step S254: performing a benchmark comparison process on the noise coverage frequency range data based on the optical signal coverage frequency range data to obtain noise abnormal spectrum data;

Step S255: fitting the abnormal side peak data and the noise abnormal spectrum data to obtain the optical signal abnormal spectrum data.

The present invention performs main wavelength identification processing on wavelength spectrum peak data to determine the fundamental wave region in the optical signal spectrum diagram, which helps to identify the main operating wavelength in the optical communication system, which is very important for subsequent channel allocation, interference management and system optimization. The main wavelength data provides basic information about the spectral emission characteristics of the light source and the channel response; the optical signal spectrum diagram is analyzed for abnormal side peaks to detect any abnormal side peaks or peaks, which helps to identify any potential interference or abnormal signals in the spectrum. The acquisition of abnormal side peak data can indicate the existence of inter-channel interference, nonlinear effects or any abnormal conditions in the optical communication system; the optical signal spectrum diagram is analyzed for abnormal noise spectrum bandwidth to determine the frequency range covered by the noise signal, which helps to evaluate the optical The noise level and nature in the communication system, by understanding the frequency range covered by the noise, can quantify the impact of noise; by benchmarking the frequency range covered by the optical signal data with the frequency range covered by the noise data, to identify the noise anomaly spectrum that is different from the basic signal characteristics, it helps to quantify the impact of noise on communication and indicates the existence of hidden channel problems or frequency band utilization problems; by fitting the abnormal side peak data and the noise anomaly spectrum data to generate comprehensive data representing the abnormal spectral characteristics of the optical signal, a concise and intuitive method is provided to represent the anomalies or interference in the optical communication system, and by fitting these data, the anomalies can be better visualized, their severity can be determined, and corresponding strategies can be formulated to minimize the impact on system performance and quality.

Preferably, step S26 comprises the following steps:

Step S261: performing abnormal side peak analysis on the abnormal spectrum data of the optical signal to obtain abnormal spectrum side peak data;

Step S262: performing abnormal communication dispersion analysis on the abnormal spectrum side peak data to obtain abnormal communication spectrum dispersion data;

Step S263: performing communication signal-to-noise impact analysis on the abnormal communication spectrum dispersion data to obtain an abnormal dispersion signal-to-noise ratio;

Step S264: performing noise communication signal-to-noise impact analysis on the optical signal abnormal spectrum data to obtain noise signal-to-noise ratio data;

Step S265: performing bit error rate analysis based on abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data to obtain communication bit error rate data;

Step S266: performing communication impact assessment processing on the communication bit error rate data to obtain spectrum abnormality communication impact data.

The present invention performs abnormal side peak analysis on abnormal spectral data of optical signals to identify abnormal side peaks in the spectral graph, which helps to reveal abnormal signals in optical communication systems, identify abnormal spectral side peaks to help locate problems, and determine whether there is interference between channels or nonlinear effects. This information is very important for ensuring system performance and signal integrity; abnormal communication dispersion analysis is performed on abnormal spectral side peak data to quantify the spectral dispersion effect experienced by optical signals during transmission, which helps to evaluate the impact of dispersion on communication quality, and by analyzing abnormal communication spectral dispersion data, the severity of dispersion and its impact on the signal-to-noise ratio can be determined; communication signal-to-noise impact analysis is performed on abnormal communication spectral dispersion data to determine the impact of dispersion on the signal-to-noise ratio, which helps to quantify the contribution of abnormal dispersion to signal quality degradation, so as to evaluate whether dispersion causes bit errors. Errors are detected and error correction technology is needed. The signal-to-noise ratio is an important indicator of system performance. Understanding the impact of dispersion is very important for optimizing optical communications. The noise communication signal-to-noise impact analysis is performed on the abnormal spectrum data of the optical signal to obtain the noise signal-to-noise ratio data. This step helps to analyze the impact of noise in the abnormal spectrum on the communication system, and provides an important reference for improving signal quality and reducing bit error rate. Bit error rate analysis is performed based on abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data to quantify the communication bit error rate, providing key indicators of system performance to evaluate the expected bit error rate under given dispersion and noise levels. The bit error rate analysis provides guidance for the design of the system's error correction mechanism and adaptive modulation schemes. By comprehensively evaluating the communication bit error rate data, the impact of abnormal signals on the communication system can be fully understood, providing an important reference for system optimization and performance improvement.

Preferably, step S3 comprises the following steps:

Step S31: performing full width measurement analysis on the optical pulse time characteristic data to obtain optical pulse width data;

Step S32: performing pulse repetition frequency analysis on the light pulse time characteristic data to obtain the pulse repetition frequency;

Step S33: constructing a time domain waveform for the optical pulse width data and the pulse repetition frequency to obtain an optical time domain waveform;

Step S34: constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve;

Step S35: Based on the optical signal spectrum diagram, an optical signal reflection curve is evaluated and analyzed for the impact of abnormality on communication, and communication impact data of abnormal optical signal reflection is obtained.

The present invention performs full-width measurement analysis on optical pulse time characteristic data to determine the duration of the optical pulse and the corresponding optical pulse width, which helps to characterize the channel occupancy properties of the optical pulse, and obtains the optical pulse width data to evaluate the pulse propagation and pulse compression characteristics in the system; performs pulse repetition frequency analysis on the optical pulse time characteristic data to determine the rate of optical pulse repetition transmission, which helps to evaluate the throughput and efficiency of the optical communication system, and the pulse repetition frequency information helps to adjust the system settings, optimize the data rate and ensure compliance with the requirements of specific applications, so as to help identify any potential frequency-related problems; performs time domain waveform construction on the optical pulse width data and the pulse repetition frequency to visualize the shape and behavior of the optical pulse in the time domain, and provide information about the optical pulse signal-to-noise ratio, distortion and potential interference, and through this time domain waveform construction, to simulate and analyze The propagation of optical pulses in the channel; by constructing a reflection curve for the node optical signal data based on the optical time domain waveform to determine the response characteristics of the system, it is helpful to analyze the channel reflection, coherence or any potential dispersion effects. By obtaining the optical signal reflection curve to evaluate the channel quality, identify the reflection source and optimize the system to minimize the reflection loss, the reflection curve construction process provides a quantitative method to characterize the reflection characteristics of the optical communication system; based on the optical signal spectrum diagram, the optical signal reflection curve is analyzed for abnormal impact communication evaluation to determine the impact of reflection anomalies on optical communication to evaluate the abnormal reflection interference and the degree of impact on effective communication. Through this evaluation, it is determined whether the reflection anomaly leads to deterioration of the signal-to-noise ratio, interference or signal quality degradation. The optical signal reflection abnormality communication impact data provides important insights for troubleshooting and performance optimization.

Preferably, step S34 includes the following steps:

Step S341: Perform fiber node analysis on the node optical signal data to obtain fiber node data;

Step S342: Perform node optical signal frequency analysis on the optical fiber node data to obtain the node optical signal frequency;

Step S343: performing reflection signal capture processing on the optical fiber node data based on the optical time domain waveform to obtain reflection signal data;

Step S344: performing reflection signal strength analysis on the reflection signal data to obtain reflection signal strength;

Step S345: Perform curve construction processing on the node optical signal data based on the node optical signal frequency and the reflected signal strength to obtain an optical signal reflection curve.

The present invention performs optical fiber node analysis on node optical signal data to identify and locate specific nodes in an optical fiber communication system, thereby helping to analyze the propagation and transmission characteristics of optical signals in an optical fiber network. The optical fiber node data, including node location, loss, and reflection characteristics, are obtained to evaluate the optical signal data at these nodes. Node optical signal frequency analysis is performed on the optical fiber node data to determine the oscillation frequency of the optical signal at the optical fiber node, thereby helping to ensure that the optical signal matches the design frequency of the node and ensures optimal transmission. Node optical signal frequency analysis helps to identify frequency mismatches and interference. Reflected signal capture processing is performed on the optical fiber node data to analyze the optical signal reflected from the node, thereby helping to quantify the characteristics of the reflected signal, including intensity, duration, and potential errors. The reflected signal data is processed to evaluate the channel quality at the node, characterize the reflection source and determine the impact on the performance of the optical communication system; the reflected signal strength is analyzed on the reflected signal data to quantify the power of the reflected signal, providing a method to measure the reflection characteristics of the optical fiber node. By analyzing the reflected signal strength, the severity of the reflected signal at the node and its potential impact on the integrity and quality of the optical signal are evaluated to help identify abnormal reflection, interference and power loss problems; the node optical signal data is processed by curve construction based on the node optical signal frequency and reflection signal strength to generate an optical signal reflection curve. Using the node optical signal frequency and reflection signal strength information, a quantitative representation is created to illustrate the relationship between the optical signal power and the reflection characteristics. The optical signal reflection curve provides valuable information for visual understanding of optical signal performance.

Preferably, step S35 includes the following steps:

Step S351: performing reflection intensity spectrum analysis on the light signal reflection curve based on the light signal spectrum diagram to obtain a reflection intensity spectrum diagram;

Step S352: performing abnormal peak drop analysis on the reflection intensity spectrum to obtain abnormal peak drop data;

Step S353: performing abnormal reflection peak increment analysis on the reflection intensity spectrum to obtain abnormal reflection peak increment data;

Step S354: performing abnormal reflection period analysis on the reflection intensity spectrum to obtain abnormal reflection period data;

Step S355: performing abnormal communication data set processing on the abnormal peak value decrease data, the abnormal reflection peak increment data and the abnormal reflection period data to obtain an abnormal reflection data set;

Step S356: analyzing the influence of the abnormal reflection data set on the optical signal flux to obtain optical signal flux influence data;

Step S357: Perform abnormal impact communication evaluation analysis on the optical signal flux impact data to obtain optical signal reflection abnormality communication impact data.

The present invention performs reflection intensity spectrum analysis on an optical signal spectrum diagram and an optical signal reflection curve to determine the intensity distribution of the reflection signal, which helps to quantify the spectrum characteristics of the reflection signal, and generates a reflection intensity spectrum diagram to intuitively display and analyze the power frequency range distribution of the reflection signal; performs abnormal peak drop analysis on the reflection intensity spectrum diagram to identify abnormal peaks or sudden drops in the spectrum, which helps to detect potential interference or attenuation in the reflection signal, and compares the expected or standard spectrum with the observed peak drop to determine the existence of abnormal reflection and its potential impact on the performance of the optical communication system; performs abnormal reflection peak increment analysis on the reflection intensity spectrum diagram to help identify abnormal peak growth in the reflection signal, and quantify the peak increment by comparing continuous spectrum lines or baseline levels, and the abnormal reflection peak increment analysis reveals the existence of channel interference sources, which affects the integrity and quality of the optical signal; performs abnormal reflection period analysis on the reflection intensity spectrum diagram to obtain abnormal reflection period data, which helps to analyze the period of the abnormal reflection signal. The periodic changes are conducive to providing detailed data on the periodicity of abnormal reflection signals, providing support for abnormal feature identification and problem location; based on the abnormal peak drop data, abnormal reflection peak increment data and abnormal reflection period data, the abnormal communication data set is processed to obtain the abnormal reflection data set, which can comprehensively analyze the various characteristics of the abnormal signal, help to comprehensively consider different characteristics, and provide comprehensive data support for the comprehensive evaluation and processing of abnormal signals; the optical signal flux impact data is evaluated and analyzed for the abnormal impact communication to determine the impact of abnormal reflection on actual optical communication, and the optical signal flux impact data is used to evaluate the ultimate consequences of abnormal reflection on signal integrity, bit error rate or transmission efficiency; the optical signal flux impact data is evaluated and analyzed for the abnormal impact communication to quantify the impact of abnormal reflection on the communication system, help identify abnormal problems in communication, and provide specific information about the impact of abnormal reflection on the communication system, providing an important reference for system operation maintenance and performance improvement.

Preferably, step S4 comprises the following steps:

Step S41: performing image fitting processing on the communication frequency graph based on the spectrum abnormality communication impact data and the optical signal reflection abnormality communication impact data to obtain a spectrum reflection frequency graph;

Step S42: performing feature analysis and indexation processing on the spectral reflection frequency graph to obtain a spectral reflection fusion index;

Step S43: analyzing the abnormality-affected communication interval on the spectrum reflection frequency diagram to obtain the spectrum reflection abnormality-affected interval;

Step S44: performing covariance analysis on the spectral reflectance fusion index based on the spectral reflectance anomaly influence interval to obtain the spectral reflectance anomaly fusion index;

Step S45: performing abnormal node identification processing on the all-optical routing node data based on the spectral reflection abnormal fusion index to obtain the all-optical routing abnormal node data;

Step S46: performing abnormal communication strategy analysis on the all-optical routing based on the abnormal node data of the all-optical routing to obtain an abnormal channel switching processing strategy.

The present invention performs image fitting processing on the data of spectral abnormal communication impact and the data of optical signal reflection abnormal communication impact to integrate the abnormal communication impact information and generate a spectral reflection frequency diagram, which is helpful to visualize and identify the existence of reflection anomalies in the frequency domain. The spectral reflection frequency diagram provides an intuitive representation of the location and degree of degradation of the performance of the optical communication system in the frequency domain; the spectral reflection frequency diagram is subjected to feature analysis and indexation processing to quantify the impact of reflection anomalies and obtain a spectral reflection fusion index, and identify key features in the spectral reflection diagram. The indexation processing provides a concise method to represent the intensity and nature of reflection anomalies, and provides a convenient data format for subsequent analysis and modeling; the spectral reflection frequency diagram is subjected to abnormal impact communication interval analysis to determine the impact interval of reflection anomalies on optical communications, which helps to identify any critical frequency and reflection anomaly frequency range, so as to evaluate the system performance within a given frequency range. The potential limitations within the range can be identified and the system design can be adjusted accordingly or appropriate mitigation strategies can be selected; covariance analysis of the spectral reflection fusion index based on the spectral reflection anomaly impact interval is helpful to evaluate the anomalies in the reflection frequency diagram through covariance analysis, provide a deeper analysis for the identification and processing of abnormal channels, and facilitate a comprehensive evaluation of the impact of abnormal reflections from multiple dimensions, providing more comprehensive data support for the processing of abnormal channels; abnormal node identification processing is performed on the all-optical routing node data based on the spectral reflection anomaly fusion index to determine the key nodes affected by reflection anomalies in the optical communication routing, and the fusion index is used as an indicator to identify those nodes that show significant reflection effects so as to adopt targeted strategies; abnormal communication strategy analysis is performed on the all-optical routing based on the all-optical routing abnormal node data, and abnormal channel switching processing strategies are formulated and optimized to minimize their impact.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

FIG1 is a schematic flow chart of the steps of the all-optical routing intelligent communication switching protection method based on MEMS technology of the present invention;

FIG2 is a schematic diagram of a detailed step flow chart of step S2 in FIG1 ;

FIG. 3 is a schematic diagram of a detailed flow chart of step S3 in FIG. 1 .

DETAILED DESCRIPTION

The present invention or the technical method of the present application is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and/or processor methods and/or microcontroller methods.

It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and/or" used herein includes any and all combinations of one or more of the listed associated items.

To achieve the above object, please refer to FIG. 1 to FIG. 3 , the present invention provides an all-optical routing intelligent communication switching protection method based on MEMS technology, comprising the following steps:

Step S1: performing optical signal data acquisition and processing on the all-optical routing through a MEMS sensor to obtain node optical signal data; performing optical pulse characteristics and spectrum analysis on the node optical signal data to obtain optical pulse time characteristic data and an optical signal spectrum diagram; performing communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram;

Step S2: Based on the node optical signal data, a peak analysis is performed on the optical signal spectrum to obtain wavelength spectrum peak data; a spectrum bandwidth coverage analysis is performed on the optical signal spectrum to obtain optical signal coverage frequency range data; based on the wavelength spectrum peak data and the optical signal coverage frequency range data, an abnormal impact communication evaluation analysis is performed on the optical signal spectrum to obtain spectrum abnormality communication impact data;

Step S3: constructing a time domain waveform for the optical pulse time characteristic data to obtain an optical time domain waveform; constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve; and evaluating and analyzing the abnormal impact of the optical signal reflection curve on communication based on the optical signal spectrum to obtain optical signal reflection abnormality communication impact data;

Step S4: Based on the spectral abnormal communication impact data and the optical signal reflection abnormal communication impact data, the communication frequency map is subjected to image fitting processing to obtain a spectral reflection frequency map; the spectral reflection frequency map is subjected to spectral reflection anomaly fusion index analysis to obtain a spectral reflection anomaly fusion index; based on the spectral reflection anomaly fusion index and the all-optical routing node data, an abnormal communication strategy analysis is performed on the all-optical routing to obtain an abnormal channel switching processing strategy.

In an embodiment of the present invention, please refer to FIG. 1, which is a schematic flow chart of a step flow of an all-optical routing intelligent communication switching protection method based on MEMS technology of the present invention. In this example, the steps of the all-optical routing intelligent communication switching protection method based on MEMS technology include:

Step S1: performing optical signal data acquisition and processing on the all-optical routing through a MEMS sensor to obtain node optical signal data; performing optical pulse characteristics and spectrum analysis on the node optical signal data to obtain optical pulse time characteristic data and an optical signal spectrum diagram; performing communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram;

The embodiment of the present invention collects optical signal data from a MEMS sensor of all-optical routing, and the data includes optical signal data from different node channels. The acquired optical signal data is processed to separate and analyze its optical pulse characteristics and spectral components, and the time characteristics (such as duration and pulse width) and spectral properties (such as peak value, passing wavelength and intensity) of the optical signal are studied in detail. The node optical signal data is processed by extracting the optical pulse time characteristic data and the optical signal spectrum diagram of the complete spectral characteristics.

Step S2: Based on the node optical signal data, a peak analysis is performed on the optical signal spectrum to obtain wavelength spectrum peak data; a spectrum bandwidth coverage analysis is performed on the optical signal spectrum to obtain optical signal coverage frequency range data; based on the wavelength spectrum peak data and the optical signal coverage frequency range data, an abnormal impact communication evaluation analysis is performed on the optical signal spectrum to obtain spectrum abnormality communication impact data;

The embodiments of the present invention determine the wavelength peak in the spectrum through peak analysis, thereby identifying potential optical signal anomalies and interference signals, and determine the frequency range covered by the optical signal by evaluating the bandwidth coverage of the spectrum. By combining the wavelength peak data and the frequency range information, the optical signal spectrum can be evaluated to detect the degree of impact of the anomaly on the optical signal communication.

Step S3: constructing a time domain waveform for the optical pulse time characteristic data to obtain an optical time domain waveform; constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve; and evaluating and analyzing the abnormal impact of the optical signal reflection curve on communication based on the optical signal spectrum to obtain optical signal reflection abnormality communication impact data;

The embodiment of the present invention pre-processes the optical pulse time characteristic data to remove noise and outliers, and then performs full-width measurement analysis on the optical pulse time characteristic data that has completed the denoising process to obtain optical pulse width data; segment the optical pulse time characteristic data, and then perform pulse repetition frequency analysis on each segment to obtain the pulse repetition frequency; use the software tool Python to construct time domain waveforms for the optical pulse width data and the pulse repetition frequency data; perform time delay analysis on the node optical signal data based on the optical time domain waveform and then perform reflection curve construction processing to obtain an optical signal reflection curve; construct an abnormal communication feature data set for the optical signal reflection curve based on the optical signal spectrum diagram, and use this data set to evaluate abnormal communication.

Step S4: Based on the spectral abnormal communication impact data and the optical signal reflection abnormal communication impact data, the communication frequency map is subjected to image fitting processing to obtain a spectral reflection frequency map; the spectral reflection frequency map is subjected to spectral reflection anomaly fusion index analysis to obtain a spectral reflection anomaly fusion index; based on the spectral reflection anomaly fusion index and the all-optical routing node data, an abnormal communication strategy analysis is performed on the all-optical routing to obtain an abnormal channel switching processing strategy.

The embodiment of the present invention generates a spectral reflection frequency map by performing image fitting processing on the communication frequency map. By analyzing the spectral reflection frequency map, the spectral reflection anomaly fusion index can be calculated according to the communication impact data of the spectral reflection anomaly and the optical signal reflection anomaly. By considering the data of the all-optical routing nodes, including the traffic, distance and network topology, the impact of abnormal communication is used to analyze the channel, and a channel switching strategy is formulated under abnormal conditions.

The present invention uses MEMS sensors to obtain optical signal data in all-optical routing and conducts a comprehensive analysis of the optical performance of the node. Optical pulse characteristics and spectral analysis provide valuable insights into the time and frequency characteristics of optical signals. Communication frequency analysis is performed on the time characteristics and spectral diagram of optical pulses to reveal any potential interference or conflict. Spectral peak analysis is performed on the node optical signal data to identify specific wavelengths in the optical signal, which helps to understand any potential wavelength-related anomalies. Spectral bandwidth coverage analysis provides the frequency range covered by the optical signal, which is very important for evaluating communication quality and potential frequency interference. Spectral peak and coverage data are combined to evaluate the impact of optical anomalies on communication. An optical time domain waveform is constructed to represent the change of the optical signal over time, which helps to detect any time-related characteristics or anomalies. The reflection curve construction based on the optical time domain waveform provides insights into the reflection characteristics of the optical signal. It is very useful for understanding network performance and identifying any interference caused by reflection. The optical signal reflection curve is combined with the spectrum diagram to evaluate the impact of reflection anomalies on communication. The spectral reflection frequency diagram is generated by image fitting processing of the communication frequency diagram, which provides a frequency domain representation of the optical signal reflection characteristics and reveals the relationship between reflection and frequency. Based on the spectral reflection frequency diagram, the spectral reflection anomaly is analyzed by fusion index to obtain the spectral reflection anomaly fusion index. The index quantifies the degree of influence of the reflection anomaly in the entire frequency range, which is beneficial to the final intelligent switching of all-optical routing. Finally, by considering the spectral reflection anomaly fusion index and all-optical routing node data, the abnormal communication strategy is analyzed and the channel switching processing strategy is formulated, which is beneficial to optimize the operation of EMES technology in the process of switching channel protection, and optimizes the optical signal abnormal operation speed to reduce the impact of mechanical components on switching channels in order to optimize the signal processing strategy.

Preferably, step S1 comprises the following steps:

Step S11: performing communication node identification processing on the all-optical routing to obtain an all-optical routing node;

The embodiment of the present invention obtains the topological structure information of the all-optical routing, including the connection relationship and node type of the network nodes, and then identifies each communication node according to the communication protocol and routing rules, including using the IP address, MAC address and unique identifier, and combines the identified communication node information with the topological structure information of the all-optical routing to obtain the all-optical routing node information.

Step S12: performing optical signal data acquisition processing on the all-optical routing node through the MEMS sensor to obtain the node optical signal data;

The embodiment of the present invention uses MEMS sensors, including photosensors, to collect optical signals of all-optical routing nodes in real time, stores the collected optical signal data in the form of digital signals, and performs data preprocessing.

Step S13: performing optical pulse time characteristic analysis on the node optical signal data to obtain optical pulse time characteristic data;

The embodiment of the present invention identifies and analyzes the characteristics of optical pulses by using digital signal processing technologies, such as threshold detection, edge detection and pulse counting; the characteristic data obtained by performing optical pulse time characteristic analysis on the collected node optical signal data mainly includes pulse width, pulse rising edge and falling edge time, and pulse repetition frequency parameters, and the obtained data parameters are classified and collected to obtain optical pulse time characteristic data.

Step S14: performing spectrum analysis on the node optical signal data to obtain an optical signal spectrum graph;

The embodiment of the present invention performs a spectral analysis on the collected node optical signal data, and uses Fourier transform or other spectrum analysis methods to convert the time domain signal into a frequency domain signal to obtain a spectral graph of the optical signal; the spectral graph can reflect the frequency characteristics of the optical signal, such as center frequency, bandwidth, and signal strength.

Step S15: Perform communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram.

The embodiment of the present invention infers the communication frequency of the node optical signal by combining the optical pulse time characteristic data and the optical signal spectrum diagram. For example, the communication frequency can be determined by analyzing the repetition frequency of the optical pulse and the center frequency of the spectrum diagram; the communication frequency information is presented in the form of an image to obtain a communication frequency diagram.

The present invention performs communication node identification processing on the all-optical routing to determine the position and identity of each node, provides accurate node information for subsequent data collection and analysis, and is beneficial to system management and monitoring; uses MEMS sensors to obtain and process optical signal data of the all-optical routing nodes, monitors the optical signal conditions of the nodes in real time, and provides a data basis for subsequent optical signal analysis and abnormal processing; performs optical pulse time feature analysis on the optical signal data of the nodes to extract the time feature data of the optical signals, which is helpful to understand the transmission speed and time characteristics of the optical signals and provides an important reference for communication frequency analysis; performs spectrum analysis on the optical signal data of the nodes to obtain the spectrum features of the optical signals, which is helpful to understand the frequency distribution of the optical signals and provides a basis for communication frequency analysis and system optimization; performs communication frequency analysis on the optical signal data of the nodes by combining the optical pulse time feature data with the optical signal spectrum; is beneficial to revealing the communication frequency patterns used in the network, and helps detect potential frequency conflicts, interferences or unused frequency bands by identifying and analyzing these frequency patterns, thereby optimizing optical communication performance and ensuring efficient spectrum utilization.

Preferably, step S15 comprises the following steps:

Step S151: performing optical phase analysis on the optical pulse time characteristic data to obtain an optical pulse phase spectrum;

The embodiment of the present invention imports the optical pulse time characteristic data into the analysis software, selects the Fourier transform to perform the phase analysis method, pre-processes the optical pulse time characteristic data, including noise reduction and detrending, performs phase analysis on the pre-processed data, and converts the optical pulse time characteristic data into an optical pulse phase spectrum, wherein the horizontal axis represents time or frequency, and the vertical axis represents the phase value.

Step S152: performing optical pulse repetition frequency analysis on the optical pulse phase spectrum to obtain the optical pulse repetition frequency;

The embodiment of the present invention imports the optical pulse phase spectrum into the analysis software, selects the frequency analysis method of power spectral density analysis, pre-processes the optical pulse phase spectrum, such as smoothing and denoising, performs frequency analysis on the pre-processed data, and obtains the optical pulse repetition frequency, that is, the frequency value with the highest frequency in the optical pulse phase spectrum, and the repetition period of the optical pulse.

Step S153: performing frequency analysis on the optical signal spectrum to obtain the optical signal spectrum frequency;

The embodiment of the present invention performs Fourier transform on the optical signal spectrum graph, performs data preprocessing according to the requirements of Fourier transform, performs optical signal spectrum frequency analysis on the preprocessed data, the optical signal spectrum frequency corresponds to the peak frequency in the spectrum graph, uses Gaussian fitting method to perform peak detection, accurately identifies the peak frequency in the spectrum graph, and obtains the optical signal spectrum frequency.

Step S154: performing communication frequency analysis on the node optical signal data based on the optical pulse repetition frequency and the optical signal spectrum frequency to obtain optical signal communication frequency data;

The embodiment of the present invention determines the modulation mode of the optical signal, including intensity modulation, by analyzing the relationship between the optical pulse repetition frequency and the optical signal spectrum frequency. For intensity modulation, the communication frequency usually corresponds to the multiple of the optical pulse repetition frequency and the sideband frequency. The extracted communication frequency information is recorded as the optical signal communication frequency data.

Step S155: Perform frequency mapping processing on the optical signal communication frequency data to obtain an optical signal communication frequency map.

The embodiment of the present invention arranges the optical signal communication frequency data in ascending order according to the frequency size, plots the sorted communication frequency data into a frequency graph, where the horizontal axis is the frequency and the vertical axis is the signal strength or power of the corresponding frequency, and adjusts the format and optimizes the annotation of the frequency graph.

The present invention performs optical phase analysis on the optical pulse time characteristic data to obtain the phase spectrum of the optical pulse and reveal the phase characteristics of the optical signal, which helps to understand the phase change of the optical pulse and detect the potential existence of phase encoding or phase modulation, providing a basis for subsequent frequency analysis; by analyzing the optical pulse phase spectrum, the repetition frequency of the optical pulse is determined to help identify the pulse characteristics of the light source and reveal the specific pulse mode used by the optical communication system. Determining the repetition frequency of the optical pulse is crucial for subsequent signal processing and analysis; performing frequency analysis on the optical signal spectrum diagram can reveal the spectrum distribution of the optical signal, by identifying the peaks in the spectrum, these peaks represent the optical communication channel and the specific frequency components that exist, and by analyzing Analyze the optical signal spectrum frequency to obtain important insights about the interference in the transmission signal or channel; integrate the optical pulse repetition frequency and optical signal spectrum frequency information to perform a comprehensive communication frequency analysis on the node optical signal data, which helps to identify the actual communication frequency used in the optical signal and reveal the frequency conversion technology. Through this frequency analysis, we can better understand the optical communication system and its operating parameters; by frequency mapping the optical signal communication frequency data to obtain an intuitive optical signal communication frequency map, it is helpful to quickly identify the communication frequency mode, frequency band usage or any potential interference in the system. The communication frequency map can provide valuable information for the design and optimization of optical communication systems, as well as the formulation of spectrum utilization and interference management strategies.

Preferably, step S2 comprises the following steps:

Step S21: dividing the node optical signal data by wavelength characteristics to obtain optical signal wavelength characteristic data;

Step S22: Analyze the optical signal spectrum based on the optical signal wavelength characteristic data to obtain a wavelength characteristic spectrum;

Step S23: performing peak analysis on the wavelength characteristic spectrum to obtain wavelength spectrum peak data;

Step S24: performing spectrum bandwidth coverage analysis on the optical signal spectrum diagram to obtain frequency range data covered by the optical signal;

Step S25: performing a spectrum abnormality analysis on the optical signal spectrum based on the wavelength spectrum peak data and the optical signal coverage frequency range data to obtain optical signal abnormal spectrum data;

Step S26: performing abnormal impact analysis on the optical signal abnormal spectrum data to obtain abnormal spectrum communication impact data.

As an embodiment of the present invention, referring to FIG. 2 , which is a detailed flow chart of step S2 in FIG. 1 , in this embodiment, step S2 includes the following steps:

Step S21: dividing the node optical signal data by wavelength characteristics to obtain optical signal wavelength characteristic data;

The embodiment of the present invention obtains node optical signal data by using a spectrometer, including intensity information of the optical signal at different wavelengths, and divides the wavelength range of the optical signal into multiple frequency bands based on the feature extraction of the spectrum graph. According to the divided frequency bands, the optical signal data is divided into different wavelength intervals, and the optical signal data in each interval is extracted to obtain the optical signal wavelength characteristic data.

Step S22: Analyze the optical signal spectrum based on the optical signal wavelength characteristic data to obtain a wavelength characteristic spectrum;

The embodiment of the present invention plots an optical signal spectrum diagram by taking the wavelength as the horizontal axis and the optical power as the vertical axis of the original optical signal data. On the optical signal spectrum diagram, the wavelength intervals divided according to the wavelength characteristics of the optical signal are marked with different colors or line types to save the marked optical signal spectrum diagram as a wavelength characteristic spectrum diagram.

Step S23: performing peak analysis on the wavelength characteristic spectrum to obtain wavelength spectrum peak data;

The embodiment of the present invention performs peak detection on the wavelength characteristic spectrum by applying the Gaussian fitting method, identifies the peak points in each wavelength characteristic interval, and records the wavelength and corresponding optical power value of each peak point as wavelength spectrum peak data.

Step S24: performing spectrum bandwidth coverage analysis on the optical signal spectrum diagram to obtain frequency range data covered by the optical signal;

The embodiment of the present invention sets an optical power threshold according to the noise level or other indicators to distinguish between signals and noise, finds the wavelength range boundary where the optical power is greater than the set threshold on the optical signal spectrum diagram, converts the wavelength range boundary into a corresponding frequency range, and obtains the optical signal coverage frequency range data.

Step S25: performing a spectrum abnormality analysis on the optical signal spectrum based on the wavelength spectrum peak data and the optical signal coverage frequency range data to obtain optical signal abnormal spectrum data;

The embodiment of the present invention defines the number of peaks, peak power range, and spectral shape characteristics in each wavelength characteristic interval according to historical data and standard specifications, establishes a normal spectrum model, compares and analyzes the wavelength spectrum peak data of the current optical signal and the frequency range data covered by the optical signal with the normal spectrum model, and identifies abnormal features that deviate from the normal model when new peaks appear, peak powers exceed the normal range, and spectral shapes are distorted, and extracts spectral data corresponding to the identified abnormal spectral features as abnormal spectral data of the optical signal.

Step S26: performing abnormal impact analysis on the optical signal abnormal spectrum data to obtain abnormal spectrum communication impact data.

The embodiment of the present invention analyzes the causes of spectral anomalies based on the characteristics of abnormal spectral data of optical signals in combination with the structure and working principle of the optical transmission system, and evaluates the impact of spectral anomalies on communication performance resulting in increased bit error rate and shortened transmission distance according to the causes of the anomalies and the degree of spectral anomalies. The impact of spectral anomalies on communication performance is quantified into specific indicators, including bit error rate and transmission distance, and data is integrated to obtain spectral anomaly communication impact data.

The present invention divides the wavelength characteristics of the node optical signal data and accurately extracts the key information about the wavelength of the optical signal, which provides important support for determining the different wavelengths used in the optical communication system. The acquisition of wavelength characteristic data is crucial for in-depth understanding of the characteristics of the optical signal and the wavelength-related effects in the optical channel, which is helpful for system design and performance optimization. Based on the wavelength characteristic data of the optical signal, the spectrum analysis is performed to obtain the wavelength characteristic spectrum diagram, which can accurately describe the spectrum characteristics of the optical signal at different wavelengths and provide key clues for further analysis. By performing peak analysis on the wavelength characteristic spectrum diagram and obtaining the wavelength spectrum peak data, the peak characteristics in the spectrum can be accurately identified, providing an important reference for abnormal analysis and signal optimization; the spectrum bandwidth coverage analysis can determine the entire frequency range covered by the optical signal, which helps to make full use of spectrum resources and discover the existence of different channels and frequency ranges; by understanding the frequency range covered by the optical signal in detail, it can provide important data for the evaluation of the system bandwidth requirements, optimize communication performance, and improve system stability and efficiency. These comprehensive analysis steps help to fully understand the wavelength characteristics and frequency distribution of the optical signal, provide key support for the design and optimization of the optical communication system, further improve the reliability and performance of the communication system, and promote the development of optical communication technology.

Preferably, step S25 comprises the following steps:

Step S251: performing main wavelength identification processing on the optical signal spectrum diagram based on the wavelength spectrum peak data to obtain main wavelength data of the spectrum;

The embodiment of the present invention analyzes the optical power value corresponding to each peak according to the wavelength spectrum peak data, sorts the peaks from high to low according to the power value, sets the main peak discrimination threshold according to the various optical signal information data characteristics in the actual all-optical routing communication, and selects the wavelength corresponding to the peak that meets the main peak discrimination threshold as the main wavelength data of the spectrum.

Step S252: performing abnormal side peak analysis on the optical signal spectrum based on the main wavelength data of the spectrum to obtain abnormal side peak data;

The embodiment of the present invention sets a wavelength range as the side peak analysis range with the main wavelength of the spectrum as the center. Within the side peak analysis range, other peaks except the main wavelength peak are identified. These peaks are potential abnormal side peaks. According to the side peak judgment standard of the preset side peak power threshold, it is judged whether the identified side peak is an abnormal side peak, and the wavelength and power information of the abnormal side peak are recorded as abnormal side peak data.

Step S253: performing abnormal noise spectrum bandwidth analysis on the optical signal spectrum to obtain noise coverage frequency range data;

In the embodiment of the present invention, a moving average filter is used to smooth the optical signal spectrum to reduce the influence of noise on the analysis result. A noise threshold is set according to the overall trend and noise level of the spectrum to distinguish between signal and noise, and the frequency range in which the power of the spectrum is lower than the noise threshold is identified. This frequency range is used as the noise coverage frequency range data.

Step S254: performing a benchmark comparison process on the noise coverage frequency range data based on the optical signal coverage frequency range data to obtain noise abnormal spectrum data;

The embodiment of the present invention identifies the noise frequency range that exceeds the normal optical signal coverage range by comparing the optical signal coverage frequency range data and the noise coverage frequency range data. The noise frequency range that exceeds the normal optical signal coverage range is identified as abnormal noise, and the frequency range and power information corresponding to the abnormal noise are extracted as noise abnormality spectrum data.

Step S255: fitting the abnormal side peak data and the noise abnormal spectrum data to obtain the optical signal abnormal spectrum data.

The embodiment of the present invention integrates the abnormal side peak data and the noise abnormal spectrum data to obtain a data set containing all abnormal spectrum information, fits the abnormal spectrum data to obtain a fitting curve describing the abnormal spectrum characteristics, extracts the spectrum data corresponding to the fitting curve, and obtains the optical signal abnormal spectrum data.

The present invention performs main wavelength identification processing on wavelength spectrum peak data to determine the fundamental wave region in the optical signal spectrum diagram, which helps to identify the main operating wavelength in the optical communication system, which is very important for subsequent channel allocation, interference management and system optimization. The main wavelength data provides basic information about the spectral emission characteristics of the light source and the channel response; the optical signal spectrum diagram is analyzed for abnormal side peaks to detect any abnormal side peaks or peaks, which helps to identify any potential interference or abnormal signals in the spectrum. The acquisition of abnormal side peak data can indicate the existence of inter-channel interference, nonlinear effects or any abnormal conditions in the optical communication system; the optical signal spectrum diagram is analyzed for abnormal noise spectrum bandwidth to determine the frequency range covered by the noise signal, which helps to evaluate the optical The noise level and nature in the communication system, by understanding the frequency range covered by the noise, can quantify the impact of noise; by benchmarking the frequency range covered by the optical signal data with the frequency range covered by the noise data, to identify the noise anomaly spectrum that is different from the basic signal characteristics, it helps to quantify the impact of noise on communication and indicates the existence of hidden channel problems or frequency band utilization problems; by fitting the abnormal side peak data and the noise anomaly spectrum data to generate comprehensive data representing the abnormal spectral characteristics of the optical signal, a concise and intuitive method is provided to represent the anomalies or interference in the optical communication system, and by fitting these data, the anomalies can be better visualized, their severity can be determined, and corresponding strategies can be formulated to minimize the impact on system performance and quality.

Preferably, step S26 comprises the following steps:

Step S261: performing abnormal side peak analysis on the abnormal spectrum data of the optical signal to obtain abnormal spectrum side peak data;

The embodiment of the present invention identifies peaks whose power is significantly higher than the surrounding noise level in the optical signal abnormal spectrum data as abnormal side peaks, and records the central wavelength, peak power, and bandwidth information of each abnormal side peak as abnormal spectrum side peak data.

Step S262: performing abnormal communication dispersion analysis on the abnormal spectrum side peak data to obtain abnormal communication spectrum dispersion data;

The embodiment of the present invention establishes an optical fiber dispersion model according to parameters such as the type and length of the optical fiber. The model describes the dispersion characteristics of optical signals of different wavelengths when transmitted in the optical fiber. Based on the dispersion model and the central wavelength information in the abnormal spectral side peak data, the group velocity dispersion of each abnormal side peak is calculated to represent the corresponding dispersion value. The central wavelength, peak power and corresponding dispersion value of each abnormal side peak are integrated together to form abnormal communication spectral dispersion data.

Step S263: performing communication signal-to-noise impact analysis on the abnormal communication spectrum dispersion data to obtain an abnormal dispersion signal-to-noise ratio;

The embodiment of the present invention calculates the broadening effect of each abnormal side peak on the optical pulse based on the dispersion value in the abnormal communication spectral dispersion data, calculates the signal-to-noise ratio loss caused by each abnormal side peak according to the pulse broadening effect and in combination with parameters such as the receiver bandwidth of the optical communication system, and performs weighted averaging of the signal-to-noise ratio loss of each abnormal side peak and its peak power to obtain the abnormal dispersion signal-to-noise ratio that comprehensively considers the influence of all abnormal side peaks.

Step S264: performing noise communication signal-to-noise impact analysis on the optical signal abnormal spectrum data to obtain noise signal-to-noise ratio data;

The embodiment of the present invention integrates the noise part except the abnormal side peak in the abnormal spectrum data of the optical signal to obtain the total noise power, compares the main peak power of the optical signal with the total noise power, and calculates the signal-to-noise ratio of the optical signal.

Step S265: performing bit error rate analysis based on abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data to obtain communication bit error rate data;

The embodiment of the present invention selects a bit error rate model of the BER curve model according to the modulation format, coding method and other parameters of the optical communication system, substitutes the abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data into the bit error rate model, and calculates the bit error rate of the optical communication system.

Step S266: performing communication impact assessment processing on the communication bit error rate data to obtain spectrum abnormality communication impact data.

The embodiment of the present invention compares the calculated bit error rate with the bit error rate impact data degree of the optical communication system to determine the interval in which the communication quality is degraded due to the spectrum anomaly. According to the bit error rate impact data degree, the influence of the spectrum anomaly on the communication quality is analyzed and quantified to obtain the spectrum anomaly communication impact data.

The present invention performs abnormal side peak analysis on abnormal spectral data of optical signals to identify abnormal side peaks in the spectral graph, which helps to reveal abnormal signals in optical communication systems, identify abnormal spectral side peaks to help locate problems, and determine whether there is interference between channels or nonlinear effects. This information is very important for ensuring system performance and signal integrity; abnormal communication dispersion analysis is performed on abnormal spectral side peak data to quantify the spectral dispersion effect experienced by optical signals during transmission, which helps to evaluate the impact of dispersion on communication quality, and by analyzing abnormal communication spectral dispersion data, the severity of dispersion and its impact on the signal-to-noise ratio can be determined; communication signal-to-noise impact analysis is performed on abnormal communication spectral dispersion data to determine the impact of dispersion on the signal-to-noise ratio, which helps to quantify the contribution of abnormal dispersion to signal quality degradation, so as to evaluate whether dispersion causes bit errors. Errors are detected and error correction technology is needed. The signal-to-noise ratio is an important indicator of system performance. Understanding the impact of dispersion is very important for optimizing optical communications. The noise communication signal-to-noise impact analysis is performed on the abnormal spectrum data of the optical signal to obtain the noise signal-to-noise ratio data. This step helps to analyze the impact of noise in the abnormal spectrum on the communication system, and provides an important reference for improving signal quality and reducing bit error rate. Bit error rate analysis is performed based on abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data to quantify the communication bit error rate, providing key indicators of system performance to evaluate the expected bit error rate under given dispersion and noise levels. The bit error rate analysis provides guidance for the design of the system's error correction mechanism and adaptive modulation schemes. By comprehensively evaluating the communication bit error rate data, the impact of abnormal signals on the communication system can be fully understood, providing an important reference for system optimization and performance improvement.

Preferably, step S3 comprises the following steps:

Step S31: performing full width measurement analysis on the optical pulse time characteristic data to obtain optical pulse width data;

Step S32: performing pulse repetition frequency analysis on the light pulse time characteristic data to obtain the pulse repetition frequency;

Step S33: constructing a time domain waveform for the optical pulse width data and the pulse repetition frequency to obtain an optical time domain waveform;

Step S34: constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve;

Step S35: Based on the optical signal spectrum diagram, an optical signal reflection curve is evaluated and analyzed for the impact of abnormality on communication, and communication impact data of abnormal optical signal reflection is obtained.

As an embodiment of the present invention, referring to FIG. 2 , which is a detailed flow chart of step S3 in FIG. 1 , in this embodiment, step S3 includes the following steps:

Step S31: performing full width measurement analysis on the optical pulse time characteristic data to obtain optical pulse width data;

The embodiment of the present invention analyzes the time characteristic data of the optical pulse to find the starting points of the rising edge and the falling edge of the pulse, which can usually be set as a threshold point that exceeds a certain proportion of the noise level. Based on the identified starting points of the rising edge and the falling edge of the pulse, the duration of the pulse, that is, the pulse width, is calculated.

Step S32: performing pulse repetition frequency analysis on the light pulse time characteristic data to obtain the pulse repetition frequency;

The embodiment of the present invention identifies periodically occurring pulse sequences in the optical pulse time characteristic data and measures the time interval between adjacent pulses. The pulse repetition frequency is the inverse of the pulse interval, indicating the number of pulses occurring per unit time.

Step S33: constructing a time domain waveform for the optical pulse width data and the pulse repetition frequency to obtain an optical time domain waveform;

The embodiment of the present invention generates a pulse sequence evenly distributed on the time axis according to the pulse repetition frequency, selects a function to simulate the pulse shape according to the shape of the actual optical pulse, including a Gaussian function and a rectangular function, scales the simulated pulse shape according to the obtained pulse width, and fills it into the time point corresponding to the pulse sequence to form a complete optical time domain waveform.

Step S34: constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve;

The embodiment of the present invention performs a time domain convolution operation on the optical time domain waveform and the node optical signal data. The convolution result reflects the reflection condition of the optical signal on the transmission path. The reflection is identified based on information such as the peak position and intensity. The optical signal reflection curve is plotted with time as the horizontal coordinate and the reflected signal intensity as the vertical coordinate.

Step S35: Based on the optical signal spectrum diagram, an optical signal reflection curve is evaluated and analyzed for the impact of abnormality on communication, and communication impact data of abnormal optical signal reflection is obtained.

The embodiment of the present invention identifies reflection peaks exceeding a preset threshold in an optical signal reflection curve. These peaks represent abnormal reflection events. The time at which the reflection peaks occur is associated with the spectrum information of the corresponding time point in the optical signal spectrum diagram. The influence of the reflection events on the communication quality is evaluated based on the reflection peak intensity, the reflection wavelength range, and the parameters of the optical communication system. The influence includes causing signal distortion, power loss, and increased bit error rate. The evaluation results are quantified into specific indicators to form communication impact data of abnormal optical signal reflection.

The present invention performs full-width measurement analysis on optical pulse time characteristic data to determine the duration of the optical pulse and the corresponding optical pulse width, which helps to characterize the channel occupancy properties of the optical pulse, and obtains the optical pulse width data to evaluate the pulse propagation and pulse compression characteristics in the system; performs pulse repetition frequency analysis on the optical pulse time characteristic data to determine the rate of optical pulse repetition transmission, which helps to evaluate the throughput and efficiency of the optical communication system, and the pulse repetition frequency information helps to adjust the system settings, optimize the data rate and ensure compliance with the requirements of specific applications, so as to help identify any potential frequency-related problems; performs time domain waveform construction on the optical pulse width data and the pulse repetition frequency to visualize the shape and behavior of the optical pulse in the time domain, and provide information about the optical pulse signal-to-noise ratio, distortion and potential interference, and through this time domain waveform construction, to simulate and analyze The propagation of optical pulses in the channel; by constructing a reflection curve for the node optical signal data based on the optical time domain waveform to determine the response characteristics of the system, it is helpful to analyze the channel reflection, coherence or any potential dispersion effects. By obtaining the optical signal reflection curve to evaluate the channel quality, identify the reflection source and optimize the system to minimize the reflection loss, the reflection curve construction process provides a quantitative method to characterize the reflection characteristics of the optical communication system; based on the optical signal spectrum diagram, the optical signal reflection curve is analyzed for abnormal impact communication evaluation to determine the impact of reflection anomalies on optical communication to evaluate the abnormal reflection interference and the degree of impact on effective communication. Through this evaluation, it is determined whether the reflection anomaly leads to deterioration of the signal-to-noise ratio, interference or signal quality degradation. The optical signal reflection abnormality communication impact data provides important insights for troubleshooting and performance optimization.

Preferably, step S34 includes the following steps:

Step S341: Perform fiber node analysis on the node optical signal data to obtain fiber node data;

The embodiment of the present invention identifies characteristic information of each node in the optical fiber link, such as node type and node position, by analyzing the node optical signal data, and extracts the identified node characteristic information to form optical fiber node data.

Step S342: Perform node optical signal frequency analysis on the optical fiber node data to obtain the node optical signal frequency;

The embodiment of the present invention intercepts the signal segment at the corresponding node from the original optical signal data according to the node position information in the optical fiber node data, performs spectrum analysis on it, obtains the optical signal spectrum at the node, performs peak detection on the node optical signal spectrum, and identifies the main frequency components.

Step S343: performing reflection signal capture processing on the optical fiber node data based on the optical time domain waveform to obtain reflection signal data;

The embodiment of the present invention calculates the time window in which the reflected signal appears at each node based on the node position information in the optical fiber node data and the transmission speed of the optical signal in the optical fiber. In the optical time domain waveform, a signal segment within the time window corresponding to each node is intercepted, and the signal segment contains the reflected signal information at the node.

Step S344: performing reflection signal strength analysis on the reflection signal data to obtain reflection signal strength;

The embodiment of the present invention performs low-pass filtering on the reflected signal data to remove the influence of background noise, performs peak detection on the filtered reflected signal data, and obtains the reflected signal strength value at each node.

Step S345: Perform curve construction processing on the node optical signal data based on the node optical signal frequency and the reflected signal strength to obtain an optical signal reflection curve.

The embodiment of the present invention establishes a light signal reflection curve coordinate system by taking the optical fiber link length or node position as the horizontal coordinate and the reflection signal strength as the vertical coordinate. According to the node position information and the reflection signal strength value in the optical fiber node data, the corresponding points are drawn in the coordinate system, and the adjacent reflection points are connected using a smooth curve or a broken line to form a complete light signal reflection curve.

The present invention performs optical fiber node analysis on node optical signal data to identify and locate specific nodes in an optical fiber communication system, thereby helping to analyze the propagation and transmission characteristics of optical signals in an optical fiber network. The optical fiber node data, including node location, loss, and reflection characteristics, are obtained to evaluate the optical signal data at these nodes. Node optical signal frequency analysis is performed on the optical fiber node data to determine the oscillation frequency of the optical signal at the optical fiber node, thereby helping to ensure that the optical signal matches the design frequency of the node and ensures optimal transmission. Node optical signal frequency analysis helps to identify frequency mismatches and interference. Reflected signal capture processing is performed on the optical fiber node data to analyze the optical signal reflected from the node, thereby helping to quantify the characteristics of the reflected signal, including intensity, duration, and potential errors. The reflected signal data is processed to evaluate the channel quality at the node, characterize the reflection source and determine the impact on the performance of the optical communication system; the reflected signal strength is analyzed on the reflected signal data to quantify the power of the reflected signal, providing a method to measure the reflection characteristics of the optical fiber node. By analyzing the reflected signal strength, the severity of the reflected signal at the node and its potential impact on the integrity and quality of the optical signal are evaluated to help identify abnormal reflection, interference and power loss problems; the node optical signal data is processed by curve construction based on the node optical signal frequency and reflection signal strength to generate an optical signal reflection curve. Using the node optical signal frequency and reflection signal strength information, a quantitative representation is created to illustrate the relationship between the optical signal power and the reflection characteristics. The optical signal reflection curve provides valuable information for visual understanding of optical signal performance.

Preferably, step S35 includes the following steps:

Step S351: performing reflection intensity spectrum analysis on the light signal reflection curve based on the light signal spectrum diagram to obtain a reflection intensity spectrum diagram;

The embodiment of the present invention divides the entire spectral range into multiple intervals according to the wavelength based on the characteristics of the optical signal spectrum graph. For each spectrum interval, the sum of the reflection signal intensities of all reflection points in the interval is calculated as the reflection intensity value of the interval. The reflection intensity spectrum graph is drawn with the spectrum interval as the horizontal axis and the reflection intensity value as the vertical axis.

Step S352: performing abnormal peak drop analysis on the reflection intensity spectrum to obtain abnormal peak drop data;

The embodiment of the present invention identifies the main peaks with higher power in the reflection intensity spectrum diagram, compares it with the reflection intensity spectrum diagram under normal conditions, calculates the power reduction amplitude of each main peak, records each main peak frequency and the corresponding power reduction amplitude, and forms abnormal peak reduction data.

Step S353: performing abnormal reflection peak increment analysis on the reflection intensity spectrum to obtain abnormal reflection peak increment data;

The embodiment of the present invention identifies the main peak with higher power in the reflection intensity spectrum diagram, compares the current reflection intensity spectrum diagram with the reference spectrum diagram, identifies the newly added reflection peak, records the frequency, peak power and location information of each newly added peak, and forms abnormal reflection peak incremental data.

Step S354: performing abnormal reflection period analysis on the reflection intensity spectrum to obtain abnormal reflection period data;

The embodiment of the present invention obtains the periodic information of the reflection signal by performing Fourier transform on the reflection intensity spectrum diagram, converting it from the frequency domain to the time domain. In the transformed spectrum diagram, the peak value exceeding the preset threshold is identified, and the frequency, amplitude and other information corresponding to each abnormal periodic peak value are recorded to form abnormal reflection period data.

Step S355: performing abnormal communication data set processing on the abnormal peak value decrease data, the abnormal reflection peak increment data and the abnormal reflection period data to obtain an abnormal reflection data set;

The embodiment of the present invention integrates the abnormal peak drop data, the abnormal reflection peak increment data and the abnormal reflection period data to form a data set containing all abnormal reflection information.

Step S356: analyzing the influence of the abnormal reflection data set on the optical signal flux to obtain optical signal flux influence data;

The embodiment of the present invention calculates the signal power loss caused by reflection in each spectrum interval according to the peak drop data in the abnormal reflection data set, accumulates the power loss in each spectrum interval, and obtains the total optical signal flux change.

Step S357: Perform abnormal impact communication evaluation analysis on the optical signal flux impact data to obtain optical signal reflection abnormality communication impact data.

The embodiment of the present invention correlates the optical signal flux change with the receiver sensitivity, bit error rate requirements and other parameters of the optical communication system, determines whether the optical signal flux change bit error rate exceeds the standard and the number of signal interruptions, performs an abnormal impact assessment and analysis on communication, and obtains the communication impact data of the optical signal reflection abnormality.

The present invention performs reflection intensity spectrum analysis on an optical signal spectrum diagram and an optical signal reflection curve to determine the intensity distribution of the reflection signal, which helps to quantify the spectrum characteristics of the reflection signal, and generates a reflection intensity spectrum diagram to intuitively display and analyze the power frequency range distribution of the reflection signal; performs abnormal peak drop analysis on the reflection intensity spectrum diagram to identify abnormal peaks or sudden drops in the spectrum, which helps to detect potential interference or attenuation in the reflection signal, and compares the expected or standard spectrum with the observed peak drop to determine the existence of abnormal reflection and its potential impact on the performance of the optical communication system; performs abnormal reflection peak increment analysis on the reflection intensity spectrum diagram to help identify abnormal peak growth in the reflection signal, and quantify the peak increment by comparing continuous spectrum lines or baseline levels, and the abnormal reflection peak increment analysis reveals the existence of channel interference sources, which affects the integrity and quality of the optical signal; performs abnormal reflection period analysis on the reflection intensity spectrum diagram to obtain abnormal reflection period data, which helps to analyze the period of the abnormal reflection signal. The periodic changes are conducive to providing detailed data on the periodicity of abnormal reflection signals, providing support for abnormal feature identification and problem location; based on the abnormal peak drop data, abnormal reflection peak increment data and abnormal reflection period data, the abnormal communication data set is processed to obtain the abnormal reflection data set, which can comprehensively analyze the various characteristics of the abnormal signal, help to comprehensively consider different characteristics, and provide comprehensive data support for the comprehensive evaluation and processing of abnormal signals; the optical signal flux impact data is evaluated and analyzed for the abnormal impact communication to determine the impact of abnormal reflection on actual optical communication, and the optical signal flux impact data is used to evaluate the ultimate consequences of abnormal reflection on signal integrity, bit error rate or transmission efficiency; the optical signal flux impact data is evaluated and analyzed for the abnormal impact communication to quantify the impact of abnormal reflection on the communication system, help identify abnormal problems in communication, and provide specific information about the impact of abnormal reflection on the communication system, providing an important reference for system operation maintenance and performance improvement.

Preferably, step S4 comprises the following steps:

Step S41: performing image fitting processing on the communication frequency graph based on the spectrum abnormality communication impact data and the optical signal reflection abnormality communication impact data to obtain a spectrum reflection frequency graph;

The embodiment of the present invention forms two new data layers by respectively mapping the spectral abnormality communication impact data and the optical signal reflection abnormality communication impact data to the frequency points corresponding to the communication frequency diagram, and selects the weighted average method for image fusion, and fuses the two data layers together to generate a new image, namely, the spectral reflection frequency diagram.

Step S42: performing feature analysis and indexation processing on the spectral reflection frequency graph to obtain a spectral reflection fusion index;

The embodiment of the present invention analyzes the spectral reflection frequency diagram to extract characteristic parameters that can reflect the degree of abnormality, including peak intensity, peak width, peak area, and frequency offset data, and standardizes the extracted characteristic parameters to fuse multiple standardized characteristic parameters into a comprehensive indicator, namely, the spectral reflection fusion index.

Step S43: analyzing the abnormality-affected communication interval on the spectrum reflection frequency diagram to obtain the spectrum reflection abnormality-affected interval;

The embodiment of the present invention sets a threshold value according to the characteristics of the spectral reflection frequency diagram and actual experience to distinguish between normal and abnormal areas, identifies the areas in the spectral reflection frequency diagram that exceed the threshold value, and these areas are the spectral reflection abnormality affected intervals, and records the frequency range and abnormality degree information corresponding to each abnormal interval.

Step S44: performing covariance analysis on the spectral reflectance fusion index based on the spectral reflectance anomaly influence interval to obtain the spectral reflectance anomaly fusion index;

The embodiment of the present invention performs weighted processing on the spectral reflection fusion index according to the frequency range and the degree of abnormality of the spectral reflection abnormality affected interval, assigns a weight to the abnormal interval, calculates the degree of abnormality corresponding to each frequency point according to the weighted spectral reflection fusion index, and obtains the spectral reflection abnormality fusion index.

Step S45: performing abnormal node identification processing on the all-optical routing node data based on the spectral reflection abnormal fusion index to obtain the all-optical routing abnormal node data;

The embodiment of the present invention associates the spectral reflection anomaly fusion index with the all-optical routing node data, counts the number and degree of abnormal frequency points associated with each node, evaluates the degree of abnormality of each node, and identifies the nodes whose abnormality exceeds a preset threshold as all-optical routing abnormal nodes.

Step S46: performing abnormal communication strategy analysis on the all-optical routing based on the abnormal node data of the all-optical routing to obtain an abnormal channel switching processing strategy.

The embodiment of the present invention analyzes the impact of abnormal nodes on optical paths and business traffic based on the abnormal node data of all-optical routing, and evaluates different channel switching strategies according to the impact range and network resource conditions, including bypassing abnormal nodes and switching to backup optical paths, and selects the strategy with the least impact on signal communication as the abnormal channel switching processing strategy.

The present invention performs image fitting processing on the data of spectral abnormal communication impact and the data of optical signal reflection abnormal communication impact to integrate the abnormal communication impact information and generate a spectral reflection frequency diagram, which is helpful to visualize and identify the existence of reflection anomalies in the frequency domain. The spectral reflection frequency diagram provides an intuitive representation of the location and degree of degradation of the performance of the optical communication system in the frequency domain; the spectral reflection frequency diagram is subjected to feature analysis and indexation processing to quantify the impact of reflection anomalies and obtain a spectral reflection fusion index, and identify key features in the spectral reflection diagram. The indexation processing provides a concise method to represent the intensity and nature of reflection anomalies, and provides a convenient data format for subsequent analysis and modeling; the spectral reflection frequency diagram is subjected to abnormal impact communication interval analysis to determine the impact interval of reflection anomalies on optical communications, which helps to identify any critical frequency and reflection anomaly frequency range, so as to evaluate the system performance within a given frequency range. The potential limitations within the range can be identified and the system design can be adjusted accordingly or appropriate mitigation strategies can be selected; covariance analysis of the spectral reflection fusion index based on the spectral reflection anomaly impact interval is helpful to evaluate the anomalies in the reflection frequency diagram through covariance analysis, provide a deeper analysis for the identification and processing of abnormal channels, and facilitate a comprehensive evaluation of the impact of abnormal reflections from multiple dimensions, providing more comprehensive data support for the processing of abnormal channels; abnormal node identification processing is performed on the all-optical routing node data based on the spectral reflection anomaly fusion index to determine the key nodes affected by reflection anomalies in the optical communication routing, and the fusion index is used as an indicator to identify those nodes that show significant reflection effects so as to adopt targeted strategies; abnormal communication strategy analysis is performed on the all-optical routing based on the all-optical routing abnormal node data, and abnormal channel switching processing strategies are formulated and optimized to minimize their impact.

Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims (10)

1. An all-optical routing intelligent communication switching protection method based on MEMS technology, characterized in that it includes the following steps: Step S1: performing optical signal data acquisition and processing on the all-optical routing through a MEMS sensor to obtain node optical signal data; performing optical pulse characteristics and spectrum analysis on the node optical signal data to obtain optical pulse time characteristic data and an optical signal spectrum diagram; performing communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram; Step S2: Based on the node optical signal data, a peak analysis is performed on the optical signal spectrum to obtain wavelength spectrum peak data; a spectrum bandwidth coverage analysis is performed on the optical signal spectrum to obtain optical signal coverage frequency range data; based on the wavelength spectrum peak data and the optical signal coverage frequency range data, an abnormal impact communication evaluation analysis is performed on the optical signal spectrum to obtain spectrum abnormality communication impact data; Step S3: constructing a time domain waveform for the optical pulse time characteristic data to obtain an optical time domain waveform; constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve; and evaluating and analyzing the abnormal impact of the optical signal reflection curve on communication based on the optical signal spectrum to obtain optical signal reflection abnormality communication impact data; Step S4: Based on the spectral abnormal communication impact data and the optical signal reflection abnormal communication impact data, the communication frequency map is subjected to image fitting processing to obtain a spectral reflection frequency map; the spectral reflection frequency map is subjected to spectral reflection anomaly fusion index analysis to obtain a spectral reflection anomaly fusion index; based on the spectral reflection anomaly fusion index and the all-optical routing node data, an abnormal communication strategy analysis is performed on the all-optical routing to obtain an abnormal channel switching processing strategy. 2. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 1 is characterized in that step S1 comprises the following steps: Step S11: performing communication node identification processing on the all-optical routing to obtain an all-optical routing node; Step S12: performing optical signal data acquisition processing on the all-optical routing node through the MEMS sensor to obtain the node optical signal data; Step S13: performing optical pulse time characteristic analysis on the node optical signal data to obtain optical pulse time characteristic data; Step S14: performing spectrum analysis on the node optical signal data to obtain an optical signal spectrum graph; Step S15: Perform communication frequency analysis on the node optical signal data based on the optical pulse time characteristic data and the optical signal spectrum diagram to obtain a communication frequency diagram. 3. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 2, characterized in that step S15 comprises the following steps: Step S151: performing optical phase analysis on the optical pulse time characteristic data to obtain an optical pulse phase spectrum; Step S152: performing optical pulse repetition frequency analysis on the optical pulse phase spectrum to obtain the optical pulse repetition frequency; Step S153: performing frequency analysis on the optical signal spectrum to obtain the optical signal spectrum frequency; Step S154: performing communication frequency analysis on the node optical signal data based on the optical pulse repetition frequency and the optical signal spectrum frequency to obtain optical signal communication frequency data; Step S155: Perform frequency mapping processing on the optical signal communication frequency data to obtain an optical signal communication frequency map. 4. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 1, characterized in that step S2 comprises the following steps: Step S21: dividing the node optical signal data by wavelength characteristics to obtain optical signal wavelength characteristic data; Step S22: Analyze the optical signal spectrum based on the optical signal wavelength characteristic data to obtain a wavelength characteristic spectrum; Step S23: performing peak analysis on the wavelength characteristic spectrum to obtain wavelength spectrum peak data; Step S24: performing spectrum bandwidth coverage analysis on the optical signal spectrum diagram to obtain frequency range data covered by the optical signal; Step S25: performing a spectrum abnormality analysis on the optical signal spectrum based on the wavelength spectrum peak data and the optical signal coverage frequency range data to obtain optical signal abnormal spectrum data; Step S26: performing abnormal impact analysis on the optical signal abnormal spectrum data to obtain abnormal spectrum communication impact data. 5. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 3, characterized in that step S25 comprises the following steps: Step S251: performing main wavelength identification processing on the optical signal spectrum diagram based on the wavelength spectrum peak data to obtain main wavelength data of the spectrum; Step S252: performing abnormal side peak analysis on the optical signal spectrum based on the main wavelength data of the spectrum to obtain abnormal side peak data; Step S253: performing abnormal noise spectrum bandwidth analysis on the optical signal spectrum to obtain noise coverage frequency range data; Step S254: performing a benchmark comparison process on the noise coverage frequency range data based on the optical signal coverage frequency range data to obtain noise abnormal spectrum data; Step S255: fitting the abnormal side peak data and the noise abnormal spectrum data to obtain the optical signal abnormal spectrum data. 6. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 4, characterized in that step S26 comprises the following steps: Step S261: performing abnormal side peak analysis on the abnormal spectrum data of the optical signal to obtain abnormal spectrum side peak data; Step S262: performing abnormal communication dispersion analysis on the abnormal spectrum side peak data to obtain abnormal communication spectrum dispersion data; Step S263: performing communication signal-to-noise impact analysis on the abnormal communication spectrum dispersion data to obtain an abnormal dispersion signal-to-noise ratio; Step S264: performing noise communication signal-to-noise impact analysis on the optical signal abnormal spectrum data to obtain noise signal-to-noise ratio data; Step S265: performing bit error rate analysis based on abnormal dispersion signal-to-noise ratio and noise signal-to-noise ratio data to obtain communication bit error rate data; Step S266: performing communication impact assessment processing on the communication bit error rate data to obtain spectrum abnormality communication impact data. 7. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 1, characterized in that step S3 comprises the following steps: Step S31: performing full width measurement analysis on the optical pulse time characteristic data to obtain optical pulse width data; Step S32: performing pulse repetition frequency analysis on the light pulse time characteristic data to obtain the pulse repetition frequency; Step S33: constructing a time domain waveform for the optical pulse width data and the pulse repetition frequency to obtain an optical time domain waveform; Step S34: constructing a reflection curve for the node optical signal data based on the optical time domain waveform to obtain an optical signal reflection curve; Step S35: Based on the optical signal spectrum diagram, an optical signal reflection curve is evaluated and analyzed for the impact of abnormality on communication, and communication impact data of abnormal optical signal reflection is obtained. 8. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 5, characterized in that step S34 comprises the following steps: Step S341: Perform fiber node analysis on the node optical signal data to obtain fiber node data; Step S342: Perform node optical signal frequency analysis on the optical fiber node data to obtain the node optical signal frequency; Step S343: performing reflection signal capture processing on the optical fiber node data based on the optical time domain waveform to obtain reflection signal data; Step S344: performing reflection signal strength analysis on the reflection signal data to obtain reflection signal strength; Step S345: Perform curve construction processing on the node optical signal data based on the node optical signal frequency and the reflected signal strength to obtain an optical signal reflection curve. 9. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 7, characterized in that step S35 comprises the following steps: Step S351: performing reflection intensity spectrum analysis on the light signal reflection curve based on the light signal spectrum diagram to obtain a reflection intensity spectrum diagram; Step S352: performing abnormal peak drop analysis on the reflection intensity spectrum to obtain abnormal peak drop data; Step S353: performing abnormal reflection peak increment analysis on the reflection intensity spectrum to obtain abnormal reflection peak increment data; Step S354: performing abnormal reflection period analysis on the reflection intensity spectrum to obtain abnormal reflection period data; Step S355: performing abnormal communication data set processing on the abnormal peak value decrease data, the abnormal reflection peak increment data and the abnormal reflection period data to obtain an abnormal reflection data set; Step S356: analyzing the influence of the abnormal reflection data set on the optical signal flux to obtain optical signal flux influence data; Step S357: Perform abnormal impact communication evaluation analysis on the optical signal flux impact data to obtain optical signal reflection abnormality communication impact data. 10. The all-optical routing intelligent communication switching protection method based on MEMS technology according to claim 1, characterized in that step S4 comprises the following steps: Step S41: performing image fitting processing on the communication frequency graph based on the spectrum abnormality communication impact data and the optical signal reflection abnormality communication impact data to obtain a spectrum reflection frequency graph; Step S42: performing feature analysis and indexation processing on the spectral reflection frequency graph to obtain a spectral reflection fusion index; Step S43: analyzing the abnormality-affected communication interval on the spectrum reflection frequency diagram to obtain the spectrum reflection abnormality-affected interval; Step S44: performing covariance analysis on the spectral reflectance fusion index based on the spectral reflectance anomaly influence interval to obtain the spectral reflectance anomaly fusion index; Step S45: performing abnormal node identification processing on the all-optical routing node data based on the spectral reflection abnormal fusion index to obtain the all-optical routing abnormal node data; Step S46: performing abnormal communication strategy analysis on the all-optical routing based on the abnormal node data of the all-optical routing to obtain an abnormal channel switching processing strategy.