CN118310626B - An Internet of Things system for monitoring fault vibration of underground high-voltage cable joints - Google Patents
An Internet of Things system for monitoring fault vibration of underground high-voltage cable joints Download PDFInfo
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- CN118310626B CN118310626B CN202410732597.2A CN202410732597A CN118310626B CN 118310626 B CN118310626 B CN 118310626B CN 202410732597 A CN202410732597 A CN 202410732597A CN 118310626 B CN118310626 B CN 118310626B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
- G01H17/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves, not provided for in the preceding groups
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/66—Testing of connections, e.g. of plugs or non-disconnectable joints
- G01R31/68—Testing of releasable connections, e.g. of terminals mounted on a printed circuit board
- G01R31/69—Testing of releasable connections, e.g. of terminals mounted on a printed circuit board of terminals at the end of a cable or a wire harness; of plugs; of sockets, e.g. wall sockets or power sockets in appliances
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Abstract
The invention discloses an underground high-voltage cable joint fault vibration monitoring internet of things system, which relates to the technical field of internet of things and comprises the following components: based on underground environment data, real-time sensing is carried out on the target high-voltage cable joint, and a real-time monitoring sensing data set is obtained; performing vibration analysis based on the real-time monitoring sensing data set, and generating a fault signal according to a vibration analysis result; transmitting a fault signal to the communication unit to trigger an alarm instruction, and transmitting an operation fault information set to the cloud platform through the communication unit based on the alarm instruction; and the cloud platform is connected with the remote data terminal, the operation fault information set is marked as alarm prompt information, and the alarm prompt information is sent to the remote data terminal for alarm notification. The invention solves the technical problems of poor fault early warning accuracy and timeliness of the cable joint in the prior art, and achieves the technical effect of improving the fault early warning accuracy and timeliness of the cable joint by monitoring vibration data of the cable joint in real time and intelligently analyzing and early warning.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to an underground high-voltage cable joint fault vibration monitoring Internet of things system.
Background
With the continuous advancement of industrial technology and the deep development of underground mining operations, underground high-voltage cables play a critical role in mining production. However, as the complexity of the mine environment and the time of use of the cable increases, the probability of cable joint failure increases. These faults, if not found and handled in time, pose a serious threat to the production safety of the mine.
Vibration is an important precursor to failure during operation of the down-hole high voltage cable. Traditional cable joint fault detection methods often rely on periodic manual inspection and off-line detection, which are not only inefficient, but also difficult to capture instantaneous or intermittent fault signals in time.
Disclosure of Invention
The application provides an underground high-voltage cable connector fault vibration monitoring Internet of things system, which is used for solving the technical problems of poor early warning accuracy and timeliness of cable connector faults in the prior art.
In view of the above problems, the application provides an Internet of things system for monitoring fault vibration of a downhole high-voltage cable connector.
The application provides an Internet of things system for monitoring fault vibration of a downhole high-voltage cable connector, which comprises the following components:
based on underground environment data, real-time sensing is carried out on the target high-voltage cable joint, and a real-time monitoring sensing data set is obtained; performing vibration analysis based on the real-time monitoring sensing data set, and generating a fault signal according to a vibration analysis result; transmitting the fault signal to a communication unit to trigger an alarm instruction, and transmitting an operation fault information set to a cloud platform through the communication unit based on the alarm instruction; and the cloud platform is connected with a remote data terminal, the operation fault information set is marked as alarm prompt information, and the alarm prompt information is sent to the remote data terminal for alarm notification.
The technical scheme provided by the application has at least the following technical effects or advantages:
Based on underground environment data, the application carries out real-time sensing on the target high-voltage cable joint to obtain a real-time monitoring sensing data set; performing vibration analysis based on the real-time monitoring sensing data set, and generating a fault signal according to a vibration analysis result; transmitting the fault signal to a communication unit to trigger an alarm instruction, and transmitting an operation fault information set to a cloud platform through the communication unit based on the alarm instruction; and the cloud platform is connected with a remote data terminal, the operation fault information set is marked as alarm prompt information, and the alarm prompt information is sent to the remote data terminal for alarm notification. The application solves the technical problems of poor fault early warning accuracy and timeliness of the cable joint in the prior art, and achieves the technical effect of improving the fault early warning accuracy and timeliness of the cable joint by monitoring vibration data of the cable joint in real time and intelligently analyzing and early warning.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of an internet of things system for monitoring fault vibration of a downhole high-voltage cable connector according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a method for monitoring the fault vibration of an underground high-voltage cable joint by using the internet of things according to the embodiment of the application.
Reference numerals illustrate: the system comprises a real-time monitoring sensing data set acquisition module 11, a vibration analysis module 12, an alarm instruction triggering module 13 and an alarm notification module 14.
Detailed Description
The application provides an underground high-voltage cable connector fault vibration monitoring internet of things system, which aims at solving the technical problems of poor fault early warning accuracy and timeliness of cable connectors in the prior art, and achieves the technical effects of improving the fault early warning accuracy and timeliness of the cable connectors by monitoring vibration data of the cable connectors in real time and intelligently analyzing and early warning.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that the terms "comprises" and "comprising," along with any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus.
In a first embodiment, as shown in fig. 1, the present application provides an internet of things system for monitoring fault vibration of a high-voltage cable joint in a well, for executing a method for monitoring fault vibration of a high-voltage cable joint in a well, as shown in fig. 2, the system includes:
The real-time monitoring sensing data set acquisition module 11 is used for carrying out real-time sensing on the target high-voltage cable joint based on underground environment data by the real-time monitoring sensing data set acquisition module 11 to acquire a real-time monitoring sensing data set;
In the embodiment of the application, the temperature and humidity sensors, the gas sensors and the like arranged at the key positions in the pit are used for monitoring the environmental parameters such as the temperature, the humidity and the gas components in the pit in real time to acquire the underground environmental data.
According to the downhole environment data, vibration sensors, temperature sensors, etc. which can adapt to severe environments and have high precision are selected. The sensors are arranged at key parts of the high-voltage cable connector, such as connecting points, bent parts and the like, so that the state of the connector can be comprehensively monitored.
After the sensor is laid, vibration, temperature and other data of the high-voltage cable connector are continuously collected at high frequency, and a real-time monitoring sensing data set is obtained.
The vibration analysis module 12 is used for performing vibration analysis based on the real-time monitoring sensing data set, and generating a fault signal according to a vibration analysis result;
In the embodiment of the application, the vibration analysis module receives the real-time monitoring sensing data set and then carries out pretreatment on the real-time monitoring sensing data set, and the quality and consistency of the data are ensured through the steps of cleaning, denoising, standardization and the like of the data.
Then, key vibration characteristics such as amplitude, frequency, phase and the like are extracted from the preprocessed data by using signal processing technologies such as Fourier transform, wavelet analysis and the like.
Based on the extracted vibration characteristics, fault identification is performed, and a fault signal is generated once abnormal vibration is detected.
The alarm instruction triggering module 13 transmits the fault signal to a communication unit to trigger an alarm instruction, and the communication unit sends an operation fault information set to a cloud platform based on the alarm instruction;
In the embodiment of the application, the alarm instruction triggering module immediately generates an alarm instruction after identifying the fault signal. The communication unit within the system is activated, which is a highly integrated wireless communication module, such as a 4G/5G module or a WiFi module. And after the communication unit is activated, a stable data transmission connection is established with the cloud platform immediately.
And the alarm instruction triggering module collects detailed information about faults, such as fault types, time stamps, position data, vibration analysis reports and the like, integrates the information into a complete operation fault information set, and finally sends the packaged operation fault information set to the cloud platform through the activated communication unit.
And the alarm notification module 14 is connected with a remote data terminal through the cloud platform, marks the operation fault information set as alarm prompt information and sends the alarm prompt information to the remote data terminal for alarm notification.
In the embodiment of the application, the alarm notification module realizes high-efficiency data communication with the cloud platform through an API or other data exchange protocols. And the alarm notification module receives and processes the operation fault information set transmitted from the vibration analysis module in real time through the cloud platform.
After receiving the operation fault information set, key information such as fault type, position, time and the like is extracted. And the complex fault data is converted into simple and clear alarm prompt information by using a natural language processing technology, so that the personnel can understand the alarm prompt information quickly.
And finally, the alarm notification module sends alarm prompt information by means of modern communication technology such as short messages, emails, mobile application push notifications and the like, so that the alarm information can reach related personnel rapidly, and the alarm notification is completed.
Further, the real-time monitoring sensing data set obtaining module 11 in the system provided in the application embodiment is further configured to:
analyzing the underground environment data by combining the position information of the target high-voltage cable connector, laying sensors on the target high-voltage cable connector, and determining the sensor laying position information and the sensor laying quantity information;
continuously acquiring a target high-voltage cable connector according to the sensor layout position information through the sensor layout quantity information, and a plurality of monitoring parameter values;
And storing the monitoring parameter values into a monitoring database according to the acquisition time sequence, and outputting the real-time monitoring sensing data set.
In the embodiment of the application, the three-dimensional position information of the target high-voltage cable connector is acquired by utilizing the modern positioning technology, such as a downhole special GPS (global positioning system) and a laser range finder.
Based on the position of the cable joint and underground environment data, key points such as stress concentration points, severe temperature change areas and the like on the cable joint are identified through data analysis and simulation.
And predicting the performance of the connector under different environmental conditions by utilizing finite element analysis or other numerical simulation methods, and determining key monitoring points capable of comprehensively reflecting the state change of the cable connector. These monitoring points are located at key locations of the joint, such as joints, bends, etc. And meanwhile, according to the severity and monitoring requirements of the underground environment, a sensor which can adapt to the environments such as high temperature, high humidity, corrosive gas and the like is selected.
And determining the optimal layout position of the sensor according to the identification of the key points and the selection of the sensor type. These locations can reflect the state changes and environmental impact of the cable joints comprehensively and accurately. And (3) carrying out space analysis by using a GIS or digital mine model to ensure the rationality and the coverage comprehensiveness of the sensor layout position. And determining the number of the sensors according to the monitored precision requirement, the coverage range of the sensors and the cost budget.
Through the steps, the sensor layout position information and the sensor layout quantity information are determined.
And installing the sensor on the target high-voltage cable connector according to the determined sensor layout positions and the number information. Meanwhile, the sensor is configured to perform continuous data acquisition, and a plurality of monitoring parameter values including vibration, temperature and pressure are acquired.
And finally, storing the collected multiple monitoring parameter values into a monitoring database according to the collection time sequence, and outputting the real-time monitoring sensing data set.
Further, the vibration analysis module 12 is further configured to:
analyzing the real-time monitoring sensing data set to generate sensing time domain data;
converting the sensing time domain data into sensing frequency domain data through a Fourier transform algorithm;
extracting a vibration spectrogram of a vibration signal based on the sensing frequency domain data;
analyzing the vibration spectrogram to perform frequency analysis, and extracting frequency characteristics according to a frequency analysis result;
the frequency characteristic is added to the vibration analysis result.
In the embodiment of the application, when analyzing the real-time monitoring sensing data set, firstly, cleaning the data to remove abnormal values, noise or irrelevant data, and ensuring the accuracy and the effectiveness of the data. And arranging the cleaned data according to a time sequence to form sensing time domain data. The sensing time domain data directly reflects the time-varying conditions of the monitored object, such as temperature, pressure, vibration and the like.
The sensing time domain data is processed using a fourier transform algorithm, such as a fast fourier transform FFT. After fourier transformation, a set of complex numbers is obtained, whose modes represent the amplitudes of the corresponding frequencies, while the argument represents the phase. And drawing the complex numbers by taking the frequency as the horizontal axis and the amplitude as the vertical axis to obtain sensing frequency domain data, namely a spectrogram of the signal.
In the sensing frequency domain data, frequency components related to vibration are identified by analyzing peaks in the observed spectrogram. And selecting a proper drawing tool, such as matplotlib library of Python, drawing a vibration spectrogram by taking the frequency as the horizontal axis and the signal amplitude as the vertical axis.
And then analyzing the vibration spectrogram to identify main frequency components in the signal, and automatically marking the main frequencies by using a peak detection algorithm. The frequency values of the main peaks in the spectrogram are recorded, and the frequency values are taken as important characteristics of the vibration signal.
In addition to specific frequency values, statistics such as standard deviation of frequency, peak to average ratio, etc. are calculated. These statistical features help describe the width, symmetry, and other morphological characteristics of the frequency distribution. And comparing the vibration spectrogram acquired in real time with a historical spectrogram or a standard spectrogram of the equipment in a normal state. Abnormal frequency components that do not coincide with normal spectrum patterns are identified. These anomaly frequencies are indicative of equipment failure or abnormal conditions.
And finally, adding the extracted frequency characteristics, amplitude, phase and other vibration parameters to a vibration analysis result.
Further, the vibration analysis module 12 is further configured to:
analyzing the frequency characteristics to obtain frequency distribution information;
performing wavelet transformation on the vibration signal through a wavelet basis function to obtain a multi-scale frequency band;
extracting a vibration change rate of the vibration signal based on the multi-scale frequency band;
Judging whether the vibration change rate of the target high-voltage cable connector is in a preset vibration interval value or not based on the frequency distribution information;
if the vibration change rate of the target high-voltage cable connector is in the preset vibration interval value, the target high-voltage cable connector is regarded as having a fault, and a fault feature set is extracted;
generating a fault signal based on the fault signature set.
In the embodiment of the application, the frequency characteristics extracted from the vibration spectrogram are deeply analyzed by using signal processing software, and the occurrence times, the amplitude and the like of each frequency component are counted to obtain the frequency distribution information.
According to the characteristics of the vibration signal, a proper wavelet basis function, such as Daubechies wavelet, morlet wavelet and the like, is selected for wavelet transformation, and the signal is decomposed into different scales and frequencies to provide a time-frequency representation of the signal. The vibration signal is decomposed into a plurality of frequency bands by wavelet transformation, each frequency band corresponding to a particular time scale and frequency range.
The vibration change rate includes a vibration frequency change rate and a vibration amplitude change rate, and the vibration frequency change rate refers to a change rate of a main frequency component in a vibration signal with time. The main frequency component is the frequency component with the largest energy in the vibration signal. The vibration amplitude change rate refers to the change rate of vibration signal amplitude with time.
And in each scale frequency band, determining a main frequency component through spectrum analysis, tracking the change of the main frequency component along with time, and calculating the change rate of the main frequency component to obtain the change rate of the vibration frequency. And in the scale frequency band, tracking the change of amplitude along with time to obtain the vibration amplitude change rate.
The preset vibration interval value is used for determining the range of vibration frequency and amplitude generated when the high-voltage cable connector fails according to historical failure data and expert experience. Comparing the calculated vibration frequency change rate and vibration amplitude change rate with a preset vibration interval value. If the vibration change rate falls within the preset vibration interval value, the target high-voltage cable joint is regarded as being faulty.
Frequency components which are not common under normal conditions or which occur significantly in the event of a fault are then identified by spectral analysis. And meanwhile, whether the amplitude of the vibration signal has abnormal fluctuation, such as sudden increase or decrease, is analyzed, and the amplitude change is obtained. For abnormal frequency components, wavelet transforms, fourier transforms, or other spectral analysis methods are utilized to identify and extract.
The amplitude variation is quantified by calculating statistics of peak, mean, standard deviation, etc. of the signal and compared with the statistics under normal conditions. Among the extracted features, those most relevant and representative to the fault condition are selected and the PCA optimized feature set is analyzed using principal components. And integrating the extracted characteristics such as abnormal frequency components, amplitude changes and the like into a fault characteristic set.
Finally, the fault feature set generates fault signals through signal processing technology, such as inverse wavelet transform, inverse Fourier transform and the like.
Further, the alarm instruction triggering module 13 is further configured to:
analyzing vibration data based on the fault signal, and setting vibration triggering conditions;
Defining a plurality of alarm levels based on the shock triggering condition;
Constructing an alarm trigger model based on the alarm levels, judging a fault signal through the alarm trigger model, and generating a judging result, wherein the judging result comprises a judging fault occurrence result and a judging fault non-occurrence result;
And generating an alarm response according to the fault occurrence judgment result, and triggering the alarm instruction according to the alarm response result.
In the embodiment of the application, firstly, the acquired fault signals are preprocessed, including filtering, noise reduction, smoothing and the like, so as to improve the quality and reliability of the signals. The fault signal is then analyzed for changes in the time domain, such as amplitude, waveform, etc., identifying abnormal patterns or periodic changes. The time domain signal is converted into a frequency domain signal by a Fourier transform method and the like, and frequency components and amplitudes of the frequency components in the signal are analyzed. Statistical features of the fault signal, such as mean, standard deviation, peak, etc., are calculated to quantify fluctuations and stability of the signal.
According to the analysis result of the vibration data, key indexes capable of reflecting the state change of the equipment, such as the amplitude of a specific frequency, the change rate of a waveform and the like, are determined. A reasonable threshold is set for each key indicator. When a certain indicator of the fault signal exceeds this threshold, the device is considered to have failed. Historical shock data is used to verify whether the set shock trigger condition is valid. And according to the verification result, adjusting and optimizing the vibration triggering condition to improve the accuracy and reliability of the alarm system.
Through the steps, setting of vibration triggering conditions is completed.
Alarms are classified into different levels, such as primary, secondary and tertiary, depending on the severity of the shock triggering condition and the actual operation of the device. A specific trigger threshold is set for each alarm level. These thresholds are based on statistical analysis of the vibration data and are set in combination with the experience and judgment of the expert.
And constructing an alarm triggering model capable of judging whether faults occur or not and the severity of the faults according to vibration data by using a machine learning algorithm such as a support vector machine, a neural network and the like. The model is trained by using the historical vibration data and the corresponding fault labels, and the performance of the model is evaluated by methods such as cross validation. And (3) inputting vibration data acquired in real time into the trained model, and outputting a judging result by the alarm triggering model to indicate whether faults occur or not and the level of the faults.
And according to different alarm levels, formulating corresponding alarm response strategies. For example, for a primary alarm, only notifications are sent to the operator; and for three-stage alarm, stopping immediately.
When the alarm triggering model judges that faults occur, corresponding alarm instructions are automatically triggered according to the fault level in the judging result. These instructions include sending alarm information, controlling equipment shut down, etc.
Further, the operation fault information set, the system includes:
performing feature extraction on the fault signal by utilizing the time domain feature to generate a first fault feature;
extracting the characteristics of the fault signals by utilizing the frequency domain characteristics to generate second fault characteristics;
based on the first fault characteristics and the second fault characteristics, carrying out fault identification by combining a cable joint fault type library, and generating a target fault type;
And constructing the operation fault information set according to the first fault characteristic, the second fault characteristic and the target fault type.
In the embodiment of the application, the time-related characteristics, such as peak value, mean value, variance, waveform factor, peak value factor, pulse factor, margin factor and the like of the signal, are directly extracted from the fault signal. These features reflect the law of variation and the fluctuation of the signal in the time domain. And integrating the extracted time domain features to form a first fault feature set. These characteristics are related to the type of failure such as loosening, wear or breakage of the cable joint.
The time domain signal is converted into a frequency domain signal by fourier transform or wavelet transform. The characteristics of the main frequency component, the amplitude of the frequency spectrum, the energy distribution and the like of the signal are analyzed in the frequency domain. The extracted frequency domain features are integrated into a second set of fault features. These characteristics are related to specific failure modes of the cable joint, electrical faults, poor contact, etc.
And comparing and matching the first fault characteristics and the second fault characteristics with information in the library according to the existing cable joint fault type library. And determining the fault type which is most in line with the current fault signal characteristics through comparison and identification, and taking the fault type as a target fault type. The cable joint fault type library comprises various fault type feature descriptions and identification standards, and the fault types comprise short circuit type, broken line type, flashover type, compound type and the like.
And finally integrating the first fault feature, the second fault feature and the target fault type to form an operation fault information set.
Further, the alarm instruction triggering module 13 is further configured to:
The data output end of the communication unit is in communication connection with the data input end of the cloud platform, and connection information is determined;
verifying connection configuration of the communication unit and the cloud platform based on the connection information, and sending the operation fault information set to the cloud platform according to the connection configuration and the alarm instruction when the connection configuration is normal;
When the connection configuration is abnormal, the communication unit and the operation log of the cloud platform are called for fault investigation, and a reset instruction is generated according to a fault investigation result;
and reconnecting the communication unit with the cloud platform according to the reset instruction.
In the embodiment of the application, the data output end of the communication unit is connected with the data input end of the cloud platform through a standard communication protocol. Once the connection is established, the system validates and saves critical connection information such as IP address, port, and communication protocol details.
And then verifying whether the connection between the communication unit and the cloud platform is normal or not by sending a test signal or a handshake request and waiting for the response of the cloud platform. And judging whether the connection state is normal according to the response of the cloud platform. If the cloud platform gives a correct response within a specified time, the connection is considered to be configured to connect normally. And then transmitting the data to the cloud platform according to the operation fault information set integrated before and the alarm instruction. And in the sending process, the safety and the efficiency of data transmission are ensured through the steps of data encapsulation, encryption, compression and the like.
When a connection abnormality such as packet loss, delay excess or connection interruption is detected, an alarm is immediately triggered. And the latest operation log is fetched from the communication unit and the log storage system of the cloud platform. These logs are centrally managed and analyzed by an ELK stack or other log management solution. The collected log data is processed and analyzed using big data analysis techniques, such as Hadoop or Spark, to identify patterns and root causes of connection anomalies. And adopting an anomaly detection algorithm to automatically identify the anomaly behavior in the log, and accurately diagnosing whether the connection is abnormal caused by configuration errors, hardware problems, network congestion or other problems.
And determining recovery measures to be taken based on the fault detection result. And according to the diagnosis result, a series of instructions for recovery operation, such as restarting the device, updating the configuration, repairing the network setting and the like, are formulated. The reset instruction is converted into an automation script to quickly perform a recovery operation. And running an automation script, and gradually executing recovery operations according to instructions, such as restarting the communication unit, clearing the cache, reconfiguring the network and the like.
And reconnecting the communication unit with the cloud platform according to the steps.
Further, the alarm notification module 14 is further configured to:
allocating alarm tags to the operation fault information sets, and identifying fault source information, fault type information and alarm level information based on the alarm tags;
Integrating the fault source information, the fault category information and the alarm level information to generate alarm prompt information, and completing the identification of an operation fault information set based on the alarm prompt information;
visually displaying the alarm prompt information and sending a display result to the remote data terminal;
And when the remote data terminal receives the alarm prompt information to feed back information, sending an information feedback result back to the cloud platform to record.
In the embodiment of the application, the operation fault information set is firstly analyzed, and key information such as error codes, abnormal descriptions, occurrence time and the like is extracted. And according to preset rules or conditions, automatically distributing corresponding alarm labels for each piece of fault information. These rules are based on error codes, specific keywords in the log, or other identifiable patterns. Each alarm tag has a unique identifier, such as a digital code, UUID, etc.
And then the unique identifier of the alarm tag is read to identify the fault information associated with the alarm tag. The fault information includes fault source information, fault type information, and alarm level information. The fault source information is the specific location or device where the fault occurred. For example, a particular tag may represent a failure of a certain server or network device. Fault type information such as hardware faults, software errors, network problems, etc. The alarm level information is divided into a first level, a second level, a third level and the like.
And sorting the collected fault source, category and alarm level information. Corresponding fields are created in the database for these information and are associated. And presetting a template of alarm prompt information, wherein the template comprises necessary fault description, equipment information, fault type and alarm level. And automatically filling placeholders in the templates according to the integrated fault information. Generating clear and accurate alarm prompt information. And finally, distributing a unique identifier for each integrated fault information set to complete the identification of the operation fault information set.
Depending on the actual requirements, a suitable visualization tool or library is selected, such as Tableau, power BI, matplotlib, etc. And determining key information to be displayed, such as fault equipment, fault type, alarm level and the like. And the diagrams and interface layouts, such as bar charts, pie charts, maps and the like, which are intuitive and easy to understand are designed, so that fault distribution conditions are displayed. And converting the integrated alarm prompt information into a data format required by the visualization tool.
The prepared data is imported into the selected visualization tool. And creating a corresponding chart according to the designed interface layout by utilizing the functions of the visualization tool. And selecting a proper sending mode, such as HTTP request, webSocket communication and the like, according to the type of the remote data terminal and the supported communication protocol. The visual interface or key diagram is converted to a format suitable for display by the remote terminal, such as HTML, pictures, or data formats supported by the particular terminal. The visualization result is then transmitted to the remote data terminal. And the remote data terminal displays the visual result on an interface of the remote data terminal after receiving the visual result.
The remote data terminal receives alarm prompt information sent by the cloud platform through a set communication mode, such as HTTP request, webSocket and the like. After checking the alarm information, the terminal operator makes corresponding processing according to the actual situation and inputs the processing result. The operator's processing results or feedback comments are formatted into a data structure that is suitable for transmission, including text, status codes, or other related data. The remote data terminal establishes a secure connection with the cloud platform through a network, and sends formatted feedback information back to the cloud platform by using an HTTP POST request, a WebSocket message or other protocols.
In summary, the embodiment of the present application has at least the following technical effects:
Based on underground environment data, the application carries out real-time sensing on the target high-voltage cable joint to obtain a real-time monitoring sensing data set; performing vibration analysis based on the real-time monitoring sensing data set, and generating a fault signal according to a vibration analysis result; transmitting the fault signal to a communication unit to trigger an alarm instruction, and transmitting an operation fault information set to a cloud platform through the communication unit based on the alarm instruction; and the cloud platform is connected with a remote data terminal, the operation fault information set is marked as alarm prompt information, and the alarm prompt information is sent to the remote data terminal for alarm notification. The application solves the technical problems of poor fault early warning accuracy and timeliness of the cable joint in the prior art, and achieves the technical effect of improving the fault early warning accuracy and timeliness of the cable joint by monitoring vibration data of the cable joint in real time and intelligently analyzing and early warning.
It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, nor the sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.
The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202410732597.2A CN118310626B (en) | 2024-06-07 | 2024-06-07 | An Internet of Things system for monitoring fault vibration of underground high-voltage cable joints |
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| CN202410732597.2A CN118310626B (en) | 2024-06-07 | 2024-06-07 | An Internet of Things system for monitoring fault vibration of underground high-voltage cable joints |
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| CN118310626A CN118310626A (en) | 2024-07-09 |
| CN118310626B true CN118310626B (en) | 2024-11-26 |
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| CN117419901A (en) * | 2023-09-18 | 2024-01-19 | 宝武装备智能科技有限公司 | Intelligent operation and maintenance on-line monitoring device for cold rolling uncoiler |
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