CN118863643A - A method and system for intelligent monitoring of cable production quality - Google Patents

Abstract

The invention discloses a method and system for intelligently monitoring the production quality of a cable, and relates to the technical field of cable production. The method and system systematically record and analyze the quality of each section of a cable through segmented detection and serial number marking, thereby improving detection efficiency. The method comprehensively evaluates the quality of the cable in all aspects through step-by-step calculation of an appearance index Wgzs, a physical difference Wlcz, and an electrical index Dqzs. The method then accurately controls and manages the quality of each section of the cable through segmented detection and abnormality marking of the cable, thereby avoiding overall rework. The method collects and integrates various parameters of the appearance index Wgzs, the physical difference Wlcz, and the electrical index Dqzs through a summary unit, thereby providing a comprehensive basis for cable quality evaluation. The method accurately identifies and locates the degree of quality problems of each section of the cable according to the number of abnormal marks and specific analysis results, thereby making production adjustments more targeted, avoiding unnecessary intervention in normal cables, and saving production resources.

Description

A method and system for intelligent monitoring of cable production quality

Technical Field

The present invention relates to the technical field of cable production, and in particular to a method and system for intelligently monitoring cable production quality.

Background Art

The cable production quality monitoring system is designed to ensure accurate monitoring and control of key parameters in the cable production process. Through real-time data collection, analysis and feedback, the system can effectively improve the stability of the production line and product quality, reduce the defective rate, and ensure that the product meets national and industry standards.

In the invention with application number 202311006596.1, the invention relates to the field of image processing technology, and specifically to an intelligent monitoring system for cable production quality, which obtains a grayscale image of the cable line surface image, performs edge detection on the grayscale image, obtains each cable boundary pixel point, and then determines the richness of the cable line surface defect shape; performs projection processing on the grayscale image, determines each cable line surface abnormal pixel point, and determines the proportion of cable line surface defect information according to the position and grayscale value of the cable line surface abnormal pixel point; determines the cable line surface significant coefficient according to the cable line surface defect shape richness, cable line surface defect information proportion, cable line surface abnormal pixel point and cable boundary pixel point, and then determines the cable line surface significant image, and finally determines the cable line quality. The present invention can accurately determine the cable line quality by performing image processing on the cable line surface image, and effectively solves the problem of inaccurate cable line production quality detection.

However, the above technical solution still has some shortcomings. In the actual production environment, the electrical and physical properties of the cable are related to its safety, reliability and compliance in practical applications, but this method cannot detect the electrical and physical properties of the cable.

Summary of the invention

Technical issues solved

In view of the deficiencies in the prior art, the present invention provides a method and system for intelligently monitoring cable production quality, which solves the problems mentioned in the above background technology.

Technical Solution

To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent monitoring system for cable production quality, including a monitoring planning module, a monitoring model establishment module, an appearance evaluation module, a physical evaluation module, an electrical evaluation module and a summary optimization module;

The monitoring planning module is used to formulate a detailed quality monitoring plan for the cable, including the equipment used for testing and the testing sequence; at the same time, all the test data are classified into corresponding data sets;

The monitoring model establishment module is used to monitor the quality of the cable in real time through the monitoring model; by collecting historical production data and the appearance parameters, physical parameters and electrical parameters of the cable, and pre-processing the data, selecting the model and performing training optimization, and finally integrating the trained model into the system;

The appearance evaluation module is used to evaluate the appearance quality of the cable, including scratches and surface unevenness; and to calculate the relevant data of the cable appearance, obtain the appearance index Wgzs and evaluate it to obtain the corresponding evaluation result;

The physical evaluation module is used to evaluate the physical properties of the cable; at the same time, the detection data of the physical properties are compared with the standard physical data through the detection model to evaluate whether the physical properties of the cable are qualified;

The electrical evaluation module is used to evaluate the electrical performance of the cable, including the electrical conductivity, insulation performance and fire resistance of the cable; and compare the electrical performance test data with the standard data to evaluate the electrical performance of the cable and obtain corresponding evaluation results;

The summary optimization module is used to summarize the data of appearance, physical properties and electrical properties; and analyze the quality problems and patterns that occur during the production process. At the same time, according to the analysis results, the production process and parameters are adjusted to improve the quality and efficiency of cable production.

Preferably, the monitoring planning module determines the quality parameters that need to be tested, including appearance parameters, physical parameters and electrical parameters, according to the production process and quality requirements of the cable, and determines the specific test items corresponding to each parameter; at the same time, the test equipment is selected according to the test items, and the test equipment components are formed and deployed in the cable production line;

Secondly, the cables are tested in sections according to their lengths and numbered as JD ₁ , JD ₂ , JD ₃ , ..., JD _n , where n represents the number of sections. Finally, the testing sequence is determined, and the cables are tested in the order of their appearance, physical properties, and electrical properties.

Preferably, the monitoring model establishment module includes a data acquisition unit, a data preprocessing unit and a model selection and training unit; the data acquisition unit is used to collect cable quality data recorded in the historical production process, and collect real-time data of each cable section in sequence according to the detection order.

Preferably, the data preprocessing unit is used to preprocess historical data and real-time data, and after dimensionless processing of the real-time data, construct an appearance data set, a physical data set and an electrical data set; the model selection and training unit selects a convolutional neural network model and performs training and optimization according to the characteristics of the data and monitoring requirements.

Preferably, the appearance evaluation module extracts the appearance data set and performs associated calculation to obtain the appearance index Wgzs, and the specific formula is as follows:

Wherein, Wzd represents integrity; Wpz represents the average outer diameter, Wjc represents the outer diameter difference, Hsl represents the number of scratches, Hmj represents the total scratch area; Wgqx represents the appearance defect value; Phd represents smoothness, Qxm represents the defect area, Qsl represents the number of defects, and Sc represents color difference;

The appearance evaluation module compares the preset appearance threshold Z with the appearance index Wgzs to generate the following evaluation results:

If the appearance index Wgzs ≥ the appearance threshold Z, it means that the cable appearance quality is qualified, has no defects, and meets or exceeds the quality requirements. At this time, the first appearance result is generated, and the physical properties of the tested cable section are continuously evaluated;

If the appearance threshold Z>appearance index Wgzs, it means that the cable appearance quality is unqualified, there are defects, and it does not meet the quality requirements. At this time, a second appearance result is generated. At this time, the abnormal part of the cable's appearance performance is processed, and the detected section of the cable is marked as abnormal.

Preferably, the physical evaluation module extracts the performance change value Xnb, the diameter difference Zjc, the impact resistance index Kcj and the elongation at break Dsc from the physical data set, and calculates and obtains the physical difference Wlcz in a related manner. The specific formula is as follows:

In the formula, Xnz represents the actual physical property value, and Xnz _sta represents the standard physical property value;

The physical evaluation module compares the preset phase difference threshold X with the physical difference Wlcz to generate the following results:

If the phase difference threshold X> the physical difference Wlcz, it means that the physical performance quality of the current cable is qualified, and the first physical result is generated at this time, and the electrical performance of the detected cable section is continuously evaluated;

If the phase difference threshold X ≤ the physical difference Wlcz, it means that the physical performance quality of the current cable is unqualified. At this time, a second physical result is generated, and the abnormal part of the physical performance of the cable is processed, and the detected section of the cable is marked as abnormal.

Preferably, the electrical evaluation module extracts the electrical data set and obtains the electrical index Dqzs by calculating using the following formula:

In the formula, Jyz represents insulation value, Ddz represents conductivity value, Nhz represents fire resistance value, and Nyz represents withstand voltage value;

The electrical evaluation module compares the preset electrical threshold C with the electrical index Dqzs to generate the following evaluation results:

If the preset electrical threshold C is less than the electrical index Dqzs, it means that the electrical performance quality of the current cable is qualified, and the first electrical result is generated at this time, and all evaluation information of the detected cable section is transmitted to the summary optimization module;

If the preset electrical threshold C ≥ electrical index Dqzs, it means that the electrical performance quality of the current cable is unqualified. At this time, a second electrical result is generated to process the abnormal electrical performance part of the detected cable section.

Preferably, the summary optimization module includes a summary unit and an optimization unit; the summary unit collects the cable's appearance index Wgzs, physical difference Wlcz and electrical index Dqzs as well as corresponding lower-level parameters and evaluation results from the appearance evaluation module, the physical evaluation module and the electrical evaluation module.

Preferably, the optimization unit optimizes the production process of the cable by summarizing the data collected by the unit; and analyzes the quality problems and solutions of each cable section in detail according to the number of abnormal marks obtained by the second appearance result, the second physical result and the second electrical result; the specific analysis results are as follows:

If there is no abnormal mark on the cable section, it means that the cable quality is normal and no improvement is needed. Continue to maintain the existing production process and management process, and conduct quality inspections and maintenance regularly.

If there is an abnormal mark on the cable section, it means that the cable quality is abnormal, but only slightly defective, and only local improvements are needed; find out the problem points for the abnormal parameters and make corresponding adjustments;

If there are two abnormal marks on the cable section, it means that the cable quality is abnormal and there are two problem points. At this time, the two abnormal parameters should be analyzed in detail to find out the common problems and make corresponding adjustments.

If there are three abnormal marks on the cable segment, it means that the cable quality is abnormal and there are serious problems, which require systematic improvement. At this time, a comprehensive inspection of the production process should be conducted, from raw materials, processes to equipment, to find out the problems and make improvements.

A method for intelligently monitoring cable production quality comprises the following steps:

Step 1: The monitoring planning module formulates a detailed quality monitoring plan for the cable, including the equipment used for testing and the testing sequence; at the same time, all the test data are classified into corresponding data sets;

Step 2: The monitoring model establishes a module to monitor the quality of the cable in real time through the monitoring model; by collecting historical production data and the appearance parameters, physical parameters and electrical parameters of the cable, and pre-processing the data, the model is selected and trained and optimized, and finally the trained model is integrated into the system;

Step 3: the appearance evaluation module evaluates the appearance quality of the cable, including scratches and surface unevenness; and performs correlation calculation on the cable appearance related data, obtains the appearance index Wgzs, and then evaluates it to obtain the corresponding evaluation result;

Step 4: the physical evaluation module evaluates the physical properties of the cable; at the same time, the test data of the physical properties are compared with the standard physical data through the test model to evaluate whether the physical properties of the cable are qualified;

Step 5: The electrical evaluation module evaluates the electrical properties of the cable, including the electrical conductivity, insulation and fire resistance of the cable; and compares the electrical performance test data with the standard data to evaluate the electrical performance of the cable and obtain corresponding evaluation results;

Step 6. The summary optimization module summarizes the data of appearance, physical properties and electrical properties; analyzes the quality problems and patterns that occur during the production process, and adjusts the production process and parameters based on the analysis results to improve the quality and efficiency of cable production.

Beneficial Effects

The present invention provides a communication network fault early warning method and system based on artificial intelligence, which has the following beneficial effects:

(1) This intelligent cable production quality monitoring method and system collects data in three dimensions, namely, appearance, physical properties and electrical properties, in real time through detection equipment components to comprehensively monitor cable quality. It also uses laser measuring instruments and laser scanners to prevent interference factors such as light changes and stains on the cable surface from affecting the accuracy of cable surface parameter calculations. It systematically records and analyzes the quality of each cable segment through segmented detection and serial number marking to improve detection efficiency. It then uses a convolutional neural network model to accurately predict and monitor cable quality through training and optimization to guide the adjustment of production processes.

(2) This intelligent cable production quality monitoring method and system comprehensively evaluates the quality of all aspects of the cable by calculating the appearance index Wgzs, physical difference Wlcz and electrical index Dqzs step by step; and then accurately controls and manages the quality of each section of the cable by performing segmented detection and abnormal marking on the cable, thereby avoiding overall rework and improving production efficiency.

(3) This intelligent cable production quality monitoring method and system collects and integrates various parameters such as appearance index Wgzs, physical difference Wlcz and electrical index Dqzs through a summary unit, providing a comprehensive basis for cable quality evaluation; the optimization unit uses these data to conduct in-depth analysis of the production process to ensure that the quality problems of each section of cable are fully considered and solved; based on the number of abnormal marks and specific analysis results, the system accurately identifies and locates the degree of quality problems of each section of cable. This accuracy makes production adjustments more targeted, avoids unnecessary intervention in normal cables, and saves production resources.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the framework structure of an intelligent monitoring system for cable production quality according to the present invention;

FIG. 2 is a schematic diagram of the steps of a method for intelligently monitoring cable production quality according to the present invention.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Example 1

Please refer to FIG1 , a cable production quality intelligent monitoring system includes a monitoring planning module, a monitoring model establishment module, an appearance evaluation module, a physical evaluation module, an electrical evaluation module and a summary optimization module;

The monitoring planning module is used to formulate a detailed quality monitoring plan for the cable, including the equipment used for testing and the testing sequence; at the same time, all the test data are classified into corresponding data sets;

The monitoring model establishment module is used to monitor the quality of the cable in real time through the monitoring model; by collecting historical production data and the appearance parameters, physical parameters and electrical parameters of the cable, and pre-processing the data, selecting the model and performing training optimization, and finally integrating the trained model into the system;

The appearance evaluation module is used to evaluate the appearance quality of the cable, including scratches and surface unevenness; and to calculate the relevant data of the cable appearance, obtain the appearance index Wgzs and evaluate it to obtain the corresponding evaluation result;

The physical evaluation module is used to evaluate the physical properties of the cable; at the same time, the detection data of the physical properties are compared with the standard physical data through the detection model to evaluate whether the physical properties of the cable are qualified;

The electrical evaluation module is used to evaluate the electrical performance of the cable, including the electrical conductivity, insulation performance and fire resistance of the cable; and compare the electrical performance test data with the standard data to evaluate the electrical performance of the cable and obtain corresponding evaluation results;

The summary optimization module is used to summarize the data of appearance, physical properties and electrical properties; and analyze the quality problems and patterns that occur during the production process. At the same time, according to the analysis results, the production process and parameters are adjusted to improve the quality and efficiency of cable production.

In this embodiment, a detailed quality monitoring plan is formulated through the monitoring planning module, and data collection and classification are established; the cable quality and model integration are monitored in real time through the monitoring model establishment module; the appearance quality is comprehensively evaluated and rapid feedback is provided through the appearance evaluation module; the physical properties are evaluated through the physical evaluation module, and the electrical performance is evaluated through the electrical evaluation module to ensure the safety and reliability of the cable during use; the data on appearance, physical properties and electrical performance are centrally summarized and analyzed through the summary optimization module, and the production process and parameters are adjusted according to the analysis results.

Example 2

Please refer to Figure 1. The monitoring planning module determines the quality parameters that need to be tested, including appearance parameters, physical parameters and electrical parameters, according to the production process and quality requirements of the cable, and determines the specific test items corresponding to each parameter; at the same time, the test equipment is selected according to the test items, and the test equipment components are formed and deployed in the cable production line;

Secondly, the cables are tested in sections according to their lengths and numbered as JD ₁ , JD ₂ , JD ₃ , ..., JD _n , where n represents the number of sections. Finally, the testing sequence is determined, and the cables are tested in the order of appearance, physical properties, and electrical properties.

In this embodiment, the monitoring planning module is used to accurately determine the detection parameters and specific detection items; the detection equipment components are effectively deployed on the cable production line to achieve real-time monitoring and feedback of cable quality parameters; the cables are tested in sections according to length and marked with serial numbers to help manage and trace the quality status of each section; the detection process is reasonably arranged according to the order of testing appearance, physical properties and electrical properties to ensure an efficient and smooth detection process.

Example 3

Please refer to Figure 1. The monitoring model establishment module includes a data acquisition unit, a data preprocessing unit and a model selection and training unit; the data acquisition unit is used to collect cable quality data recorded in the historical production process, and collect real-time data of each cable section in sequence according to the detection order.

The data preprocessing unit is used to preprocess historical data and real-time data, and after dimensionless processing of real-time data, construct an appearance data set, a physical data set and an electrical data set; the model selection and training unit selects a convolutional neural network model according to the characteristics of the data and monitoring requirements and performs training and optimization.

In this embodiment, the cable quality data recorded in the historical production process is collected and integrated through the data acquisition unit to form a comprehensive data basis; the quality data of each cable section is collected in real time according to the set detection sequence to ensure timely acquisition of the latest production information.

Example 4

Please refer to FIG. 1 . The appearance evaluation module extracts the appearance data set and calculates the appearance index Wgzs by association. The specific formula is as follows:

Wherein, Wzd represents integrity; Wpz represents the average outer diameter, Wjc represents the outer diameter difference, Hsl represents the number of scratches, Hmj represents the total scratch area; Wgqx represents the appearance defect value; Phd represents smoothness, Qxm represents the defect area, Qsl represents the number of defects, and Sc represents color difference;

The appearance evaluation module compares the preset appearance threshold Z with the appearance index Wgzs to generate the following evaluation results:

If the appearance index Wgzs ≥ the appearance threshold Z, it means that the cable appearance quality is qualified, has no defects, and meets or exceeds the quality requirements. At this time, the first appearance result is generated, and the physical properties of the tested cable section are continuously evaluated;

If the appearance threshold Z>appearance index Wgzs, it means that the cable appearance quality is unqualified, there are defects, and it does not meet the quality requirements. At this time, a second appearance result is generated. At this time, the abnormal part of the cable's appearance performance is processed, and the detected section of the cable is marked as abnormal.

In this embodiment, the outer diameter average value Wpz and the outer diameter difference value Wjc are used to detect whether there is dimensional deviation and dimensional uniformity in the production process, and are obtained by measuring with a laser measuring instrument. The laser measuring instrument is used to prevent interference factors such as light changes and stains on the cable surface from affecting the accuracy of the calculation of the appearance index Wgzs.

The number of scratches Hsl and the total area of scratches Hmj are captured and analyzed by the visual sensor in real time and calculated to evaluate the cable surface quality and determine whether it meets the appearance requirements; 3.

The smoothness Phd is collected by the visual sensor to evaluate the flatness of the cable surface and determine whether the surface is smooth, which affects the appearance quality and installation effect;

The defect area Qxm and defect quantity Qsl are collected by laser scanner to detect defects on the cable surface, including bubbles and cracks, and evaluate the impact on cable performance and life;

The color difference Sc is collected by the spectral sensor to evaluate the uniformity and consistency of the cable surface color to ensure visual consistency and aesthetics.

Example 5

Please refer to FIG. 1 . The physical evaluation module extracts the performance change value Xnb, the diameter difference Zjc, the impact resistance index Kcj and the elongation at break Dsc from the physical data set, and calculates and obtains the physical difference Wlcz in a related manner. The specific formula is as follows:

In the formula, Xnz represents the actual physical property value, and Xnz _sta represents the standard physical property value;

The physical evaluation module compares the preset phase difference threshold X with the physical difference Wlcz to generate the following results:

If the phase difference threshold X> the physical difference Wlcz, it means that the physical performance quality of the current cable is qualified, and the first physical result is generated at this time, and the electrical performance of the detected cable section is continuously evaluated;

If the phase difference threshold X ≤ the physical difference Wlcz, it means that the physical performance quality of the current cable is unqualified. At this time, a second physical result is generated, and the abnormal part of the physical performance of the cable is processed, and the detected section of the cable is marked as abnormal.

In this embodiment, by collecting the performance change value Xnb, the performance change of the cable during use is reflected, which helps to evaluate the long-term reliability and performance stability of the cable; the diameter difference Zjc is detected by the diameter measurement sensor, which reflects the change of the cable diameter during the production process, and is an important indicator for evaluating the accuracy and consistency of the cable manufacturing process; the impact resistance index Kcj is collected by the impact testing machine, which measures the resistance of the cable when it is subjected to impact or vibration, and is a key parameter for evaluating the durability and safety of the cable; the elongation at break Dsc is detected by the tensile testing machine. By detecting the elongation at break Dsc, the extension performance of the cable material under tensile loading is reflected, which is an important indicator for evaluating the strength and reliability of the material.

Example 6

Please refer to FIG. 1 . The electrical evaluation module extracts the electrical data set and calculates the electrical index Dqzs using the following formula:

In the formula, Jyz represents insulation value, Ddz represents conductivity value, Nhz represents fire resistance value, and Nyz represents withstand voltage value;

The electrical evaluation module compares the preset electrical threshold C with the electrical index Dqzs to generate the following evaluation results:

If the preset electrical threshold C is less than the electrical index Dqzs, it means that the electrical performance quality of the current cable is qualified, and the first electrical result is generated at this time, and all evaluation information of the detected cable section is transmitted to the summary optimization module;

If the preset electrical threshold C ≥ electrical index Dqzs, it means that the electrical performance quality of the current cable is unqualified. At this time, a second electrical result is generated to process the abnormal electrical performance part of the detected cable section.

In this embodiment, the insulation value Jyz is collected by an insulation resistance measuring instrument and is used to evaluate the insulation performance of the cable. By measuring the insulation resistance, the insulation capacity of the cable under the working voltage is determined; the conductivity value Ddz is collected by a conductivity measuring instrument and is used to represent the conductivity or resistance characteristics of the cable conductor. By measuring the conductivity, the quality and stability of the cable conductor can be evaluated to ensure the current transmission efficiency and the long-term reliability of the cable; the fire resistance value Nhz is collected by a combustion performance tester and is used to measure the fire resistance of the cable under fire or high temperature conditions; the withstand voltage value Nyz is collected by a high-voltage tester and is used to measure the withstand voltage capacity of the cable under high-voltage conditions. By testing the withstand voltage performance, the strength and stability of the cable insulation layer can be evaluated to ensure the safe operation of the cable system in a high-voltage environment.

Example 7

Please refer to Figure 1, the summary optimization module includes a summary unit and an optimization unit; the summary unit collects the cable's appearance index Wgzs, physical difference Wlcz and electrical index Dqzs as well as the corresponding lower parameters and evaluation results from the appearance evaluation module, physical evaluation module and electrical evaluation module.

The optimization unit optimizes the production process of the cable by collecting the data collected by the aggregation unit; and analyzes the quality problems and solutions of each cable section in detail according to the number of abnormal marks obtained from the second appearance result, the second physical result and the second electrical result; the specific analysis results are as follows:

If there is no abnormal mark on the cable section, it means that the cable quality is normal and no improvement is needed. Continue to maintain the existing production process and management process, and conduct quality inspections and maintenance regularly.

If there is an abnormal mark on the cable section, it means that the cable quality is abnormal, but only slightly defective, and only local improvements are needed; find out the problem points for the abnormal parameters and make corresponding adjustments;

If there are two abnormal marks on the cable section, it means that the cable quality is abnormal and there are two problem points. At this time, the two abnormal parameters should be analyzed in detail to find out the common problems and make corresponding adjustments.

If there are three abnormal marks on the cable segment, it means that the cable quality is abnormal and there are serious problems, which require systematic improvement. At this time, a comprehensive inspection of the production process should be conducted, from raw materials, processes to equipment, to find out the problems and make improvements.

In this embodiment, by summarizing the appearance, physical properties and electrical performance data and combining them with detailed abnormal marking analysis, accurate identification and rapid response to cable quality problems are achieved; the optimization unit adjusts the production process according to abnormal conditions, effectively improving production efficiency and product quality; systematic data collection and analysis capabilities not only improve the transparency and efficiency of the production line, but also ensure the stability and reliability of the cable within the design requirements, further strengthening the quality management and improvement capabilities in the production process.

Example 8

Please refer to FIG2 , a method for intelligently monitoring cable production quality, comprising the following steps:

Step 1: The monitoring planning module formulates a detailed quality monitoring plan for the cable, including the equipment used for testing and the testing sequence; at the same time, all the test data are classified into corresponding data sets;

Step 2: The monitoring model establishes a module to monitor the quality of the cable in real time through the monitoring model; by collecting historical production data and the appearance parameters, physical parameters and electrical parameters of the cable, and pre-processing the data, the model is selected and trained and optimized, and finally the trained model is integrated into the system;

Step 3: the appearance evaluation module evaluates the appearance quality of the cable, including scratches and surface unevenness; and performs correlation calculation on the cable appearance related data, obtains the appearance index Wgzs, and then evaluates it to obtain the corresponding evaluation result;

Step 4: the physical evaluation module evaluates the physical properties of the cable; at the same time, the test data of the physical properties are compared with the standard physical data through the test model to evaluate whether the physical properties of the cable are qualified;

Step 5: The electrical evaluation module evaluates the electrical properties of the cable, including the electrical conductivity, insulation and fire resistance of the cable; and compares the electrical performance test data with the standard data to evaluate the electrical performance of the cable and obtain corresponding evaluation results;

Step 6. The summary optimization module summarizes the data of appearance, physical properties and electrical properties; analyzes the quality problems and patterns that occur during the production process, and adjusts the production process and parameters based on the analysis results to improve the quality and efficiency of cable production.

In this embodiment, step one is used for the detailed formulation and data classification of the quality monitoring plan to ensure comprehensive monitoring and data traceability during the cable production process, and to improve the management efficiency and production quality of the production line; step two is used for the real-time monitoring model to combine historical and real-time data, optimize preprocessing and model selection, effectively predict and prevent production anomalies, and improve the real-time and accuracy of cable quality management; step three is used to identify cable surface defects through accurate appearance evaluation, reduce the time for discovering quality problems, and improve the consistency of appearance quality and customer satisfaction; step four is used for physical performance evaluation to ensure that the strength and durability of the cable meet the standard requirements, improve the reliability and service life of the product through data comparison, and reduce the risk of product quality variation; step five is used for electrical performance evaluation to ensure cable safety and stability, timely discover electrical performance anomalies, and improve product safety and market competitiveness; step six is used for the summary optimization module to accurately identify the root causes of quality problems through data aggregation and analysis, optimize production processes and parameters, continuously improve the quality and efficiency of cable production, and enhance the competitiveness and market reputation of the enterprise.

Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims (10)

1. An intelligent monitoring system for the production quality of a cable is characterized in that: the system comprises a monitoring planning module, a monitoring model setting module, an appearance evaluation module, a physical evaluation module, an electrical evaluation module and a summarizing and optimizing module;

The monitoring planning module is used for making a detailed quality monitoring plan for the cable, and comprises equipment for detection and a detection sequence; meanwhile, constructing all data classification obtained by detection into corresponding data sets;

The monitoring model setting module is used for monitoring the quality of the cable in real time through a monitoring model; the method comprises the steps of collecting historical production data, appearance parameters, physical parameters and electrical parameters of a cable, preprocessing the data, selecting a model and training and optimizing the model, and integrating the trained model into a system;

The appearance evaluation module is used for evaluating the appearance quality of the cable, including scratches and surface irregularities; carrying out associated calculation on the cable appearance related data, obtaining an appearance index Wgzs, and then evaluating to obtain a corresponding evaluation result;

The physical evaluation module is used for evaluating the physical properties of the cable; meanwhile, comparing the detection data of the physical properties with standard physical data through a detection model, and evaluating whether the physical properties of the cable are qualified or not;

The electrical evaluation module is used for evaluating electrical properties of the cable, including conductivity, insulation and fire resistance of the cable; comparing the electrical performance detection data with standard data, and evaluating the electrical performance of the cable to obtain a corresponding evaluation result;

The summarizing and optimizing module is used for summarizing the data of the appearance, the physical performance and the electrical performance; and the quality problems and rules in the production process are analyzed, and meanwhile, the production process and parameters are adjusted according to the analysis result, so that the quality and efficiency of cable production are improved.

2. The intelligent monitoring system for cable production quality of claim 1, wherein: the monitoring planning module is used for determining quality parameters to be detected, including appearance parameters, physical parameters and electrical parameters, according to the production process and quality requirements of the cable, and determining specific detection items corresponding to each parameter; meanwhile, selecting detection equipment according to detection items, forming a detection equipment assembly and arranging the detection equipment assembly on a cable production line;

Secondly, carrying out sectional detection on the cable according to the length of the cable, and carrying out serial number marking, wherein the serial numbers are respectively marked as JD ₁、JD₂、JD₃、...、JD_n, and n represents the number of sections; and finally, determining the detection sequence, and detecting according to the sequence of the appearance, the physical property and the electrical property of the cable.

3. The intelligent monitoring system for cable production quality of claim 2, wherein: the monitoring model setting module comprises a data acquisition unit, a data preprocessing unit and a model selection and training unit; the data acquisition unit is used for collecting cable quality data recorded in the historical production process and sequentially acquiring real-time data of each section of cable according to the detection sequence.

4. A cable production quality intelligent monitoring system according to claim 3, characterized in that: the data preprocessing unit is used for preprocessing historical data and real-time data, and constructing an appearance data set, a physical data set and an electrical data set after carrying out dimensionless processing on the real-time data; and the model selection and training unit selects a convolutional neural network model according to the characteristics of the data and the monitoring requirement and performs training and optimization.

5. The intelligent monitoring system for cable production quality of claim 4, wherein: the appearance evaluation module obtains an appearance index Wgzs through extracting an appearance data set and carrying out association calculation, and the specific formula is as follows:

Wherein Wzd denotes the integrity; wpz represents an average value of outer diameters, wjc represents an outer diameter difference value, hsl represents the number of scratches, and Hmj represents the total area of scratches; wgqx denotes an appearance defect value; phd represents smoothness, qxm represents defect area, qsl represents defect number, sc represents chromatic aberration;

the appearance evaluation module compares the appearance threshold Z with the appearance index Wgzs through a preset appearance threshold Z to generate the following evaluation result:

If the appearance index Wgzs is more than or equal to the appearance threshold Z, the appearance quality of the cable is qualified, no defect exists, the quality requirement is met or exceeded, a first appearance result is generated at the moment, and the detected physical performance of the section of cable is continuously evaluated;

If the appearance threshold Z is larger than the appearance index Wgzs, the appearance threshold Z is used for indicating that the appearance quality of the cable is unqualified, the cable has defects and does not meet the quality requirement, a second appearance result is generated, at the moment, the abnormal part of the appearance performance of the cable is processed, and the detected section of the cable is marked with the abnormality.

6. The intelligent monitoring system for cable production quality of claim 5, wherein: the physical evaluation module obtains a physical difference Wlcz by extracting a performance change value Xnb, a diameter difference Zjc, an impact resistance index Kcj and an elongation at break Dsc from a physical data set, and the specific formula is as follows:

wherein Xnz represents an actual physical property value, xnz _sta represents a standard physical property value;

The physical evaluation module compares the preset phase difference threshold X with the physical difference Wlcz to generate the following results:

If the difference threshold X is larger than the physical difference Wlcz, the physical performance quality of the current cable is qualified, a first physical result is generated at the moment, and the electrical performance of the detected cable section is continuously evaluated;

If the difference value X is less than or equal to the physical difference value Wlcz, the physical performance quality of the current cable is not qualified, a second physical result is generated at the moment, an abnormal part of the physical performance of the cable is processed, and the detected section of the cable is marked abnormally.

7. The intelligent monitoring system for cable production quality of claim 6, wherein: the electrical evaluation module obtains an electrical index Dqzs by extracting an electrical data set and calculating through the following formula:

Wherein Jyz denotes an insulation value, ddz denotes a conductive value, nhz denotes a fire resistance value, and Nyz denotes a withstand voltage value;

the electrical evaluation module compares the preset electrical threshold C with the electrical index Dqzs to generate the following evaluation result:

If the preset electrical threshold C is smaller than the electrical index Dqzs, the electrical performance quality of the current cable is qualified, a first electrical result is generated at the moment, and all evaluation information of the detected section of cable is transmitted to a summarizing and optimizing module;

if the preset electrical threshold C is larger than or equal to the electrical index Dqzs, the electrical performance quality of the current cable is not qualified, a second electrical result is generated at the moment, and the detected abnormal electrical performance part of the section of cable is processed.

8. The intelligent monitoring system for cable production quality of claim 7, wherein: the summarizing and optimizing module comprises a summarizing unit and an optimizing unit; the summarizing unit collects the appearance index Wgzs, the physical difference value Wlcz and the electrical index Dqzs of the cable, and corresponding lower parameters and evaluation results through the appearance evaluation module, the physical evaluation module and the electrical evaluation module.

9. The intelligent monitoring system for cable production quality of claim 8, wherein: the optimizing unit optimizes the production process of the cable through the collected data of the summarizing unit; the quality problem and the coping scheme of each section of cable are analyzed in detail according to the number of abnormal marks obtained by the second appearance result, the second physical result and the second electrical result; the specific analysis results are as follows:

If the section of cable has no abnormal mark, the cable quality is normal, and improvement is not needed; continuously maintaining the existing production process and management flow, and periodically performing quality inspection and maintenance;

If the section of cable has an abnormal mark, the cable quality is abnormal, but only has slight defects, and only needs to be locally improved; finding out a problem point according to the abnormal parameters, and correspondingly adjusting;

If the section of cable has two abnormal marks, the cable quality is abnormal and two problem points exist, at the moment, two abnormal parameters are analyzed in detail to find out common problems, and corresponding adjustment is carried out;

if the section of cable has three abnormal marks, the cable quality is abnormal, and serious problems exist, so that systematic improvement is required; at this time, the production flow is comprehensively checked, systematic investigation is carried out from raw materials, processes to equipment, and the position of the problem is found out for improvement.

10. An intelligent monitoring method for the production quality of a cable, which is characterized in that: the method comprises the following steps:

The monitoring planning module makes a detailed quality monitoring plan for the cable, including equipment used for detection and a detection sequence; meanwhile, constructing all data classification obtained by detection into corresponding data sets;

The monitoring model setting module monitors the quality of the cable in real time through a monitoring model; the method comprises the steps of collecting historical production data, appearance parameters, physical parameters and electrical parameters of a cable, preprocessing the data, selecting a model and training and optimizing the model, and integrating the trained model into a system;

Step three, the appearance evaluation module evaluates the appearance quality of the cable, including scratches and surface irregularities; carrying out associated calculation on the cable appearance related data, obtaining an appearance index Wgzs, and then evaluating to obtain a corresponding evaluation result;

step four, the physical evaluation module evaluates the physical properties of the cable; meanwhile, comparing the detection data of the physical properties with standard physical data through a detection model, and evaluating whether the physical properties of the cable are qualified or not;

step five, the electrical evaluation module evaluates the electrical performance of the cable, including the conductivity, insulation and fire resistance of the cable; comparing the electrical performance detection data with standard data, and evaluating the electrical performance of the cable to obtain a corresponding evaluation result;

Step six, the summarizing and optimizing module summarizes the data of the appearance, the physical performance and the electrical performance; and the quality problems and rules in the production process are analyzed, and meanwhile, the production process and parameters are adjusted according to the analysis result, so that the quality and efficiency of cable production are improved.