An online abnormal monitoring method and system for high-voltage cables

Abstract

The present invention discloses a method and system for online abnormal monitoring of high-voltage cables, which relates to the technical field of electrical digital data processing. The method for online abnormal monitoring of high-voltage cables includes the following steps: initial data evaluation; data transmission; post-transmission data evaluation; data real-time evaluation. The present invention obtains an acquisition data quality evaluation value from the acquired initial electromagnetic signal data. If it is less than a preset acquisition data quality threshold, the acquisition is optimized. Then, a transmission data quality evaluation value is obtained based on the initial electromagnetic signal data and the post-transmission electromagnetic signal data. If it is less than a preset transmission data quality threshold, the transmission is optimized. Finally, a data real-time evaluation value is obtained based on the acquisition data quality evaluation value, the transmission data quality evaluation value, and the transmission data. If it is less than a preset data real-time evaluation threshold, the real-time performance is optimized, improving the accuracy of online abnormal monitoring of high-voltage cables and solving the problem of low accuracy of online abnormal monitoring of high-voltage cables in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and particularly to an on-line abnormal monitoring method and system for high-voltage cables. Background Art

[0002] As an important part of modern power systems, high-voltage cables often fail due to various reasons (such as excessive electric field strength, aging of insulating materials, etc.) during actual application, which has a great impact on the normal operation of power systems. Traditional high-voltage cable fault detection methods mainly rely on manual inspections, voltage and current monitoring, etc., and have many limitations. With the development of sensor technology and data processing technology, on-line abnormal monitoring of high-voltage cables, timely detection and handling of potential faults, and the on-line abnormal monitoring method and system for high-voltage cables will be more perfect and efficient, which is of great significance for improving the stability and safety of power systems.

[0003] In the prior art, the health status of a cable is obtained by real-time monitoring of operation data, then comparative analysis is performed based on the operation data, and finally the insulation status of the cable is monitored to achieve fault warning of high-voltage cables.

[0004] For example, a method and system for mining and evaluating UHV on-line monitoring data disclosed in the invention patent announcement with the publication number of CN106557546B includes: Step 1, cleaning the duplicate data in on-line monitoring; Step 2, cleaning the abnormal data in on-line monitoring based on association rules; and Step 3, analyzing and evaluating the data quality of the on-line monitoring data after cleaning, and determining whether the thresholds of effectiveness, completeness, standardization, and redundancy are met. If so, the process ends; if not, it returns to Step 2 again.

[0005] For example, a multi-source partial discharge intelligent positioning method and system for high-voltage cables based on sensors disclosed in the invention patent announcement with the publication number of CN117932231B includes: collecting original electromagnetic signals; obtaining the signal envelope mean sequence; calculating the noise energy concentration; further calculating the amplitude-frequency range noise estimation index; obtaining the frequency component vectors of each original electromagnetic signal; calculating the signal attenuation coefficient; further calculating the periodic narrowband interference index of each original electromagnetic signal; obtaining the amplitude-frequency range noise interference index of each window of each electromagnetic signal window sequence; obtaining the adaptive noise interference index threshold of each window of each electromagnetic signal window sequence of each original electromagnetic signal at each layer according to the amplitude-frequency range noise interference index in combination with wavelet transform, obtaining the partial discharge signals of high-voltage cables, and performing intelligent positioning of high-voltage cable partial discharges.

[0006] However, during the process of implementing the technical solutions of the present invention in the embodiments of the present application, the inventors of the present application found that the above technologies have at least the following technical problems:

[0007] In the prior art, in long-distance power transmission lines, due to various reasons such as limitations in data transmission capabilities, it is difficult to implement remote monitoring, which may affect the real-time performance of on-line abnormal monitoring of high-voltage cables, resulting in low accuracy of on-line abnormal monitoring of high-voltage cables. Summary of the Invention

[0008] By providing a method and system for on-line abnormal monitoring of high-voltage cables in an embodiment of the present application, the problem of low accuracy of on-line abnormal monitoring of high-voltage cables in the prior art is solved, and the accuracy of on-line abnormal monitoring of high-voltage cables is improved.

[0009] An embodiment of the present application provides a method for on-line abnormal monitoring of high-voltage cables, including the following steps: S1, processing and evaluating the initial electromagnetic signal data of the high-voltage cable obtained by the sensor to obtain a collected data quality evaluation value, and determining whether to perform acquisition optimization based on the collected data quality evaluation value and a preset collected data quality threshold. The initial electromagnetic signal data represents a set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable, and the collected data quality evaluation value is used to quantify the quality of the collected initial electromagnetic signal data; S2, after acquisition optimization, transmitting the initial electromagnetic signal data to the cloud, and obtaining transmitted data and transmitted electromagnetic signal data. The transmitted data represents the transmission information during the data transmission process, and the transmitted electromagnetic signal data represents the data after the initial electromagnetic signal data is transmitted; S3, performing transmission evaluation based on the initial electromagnetic signal data and the transmitted electromagnetic signal data obtained after acquisition optimization to obtain a transmitted data quality evaluation value, and determining whether to perform transmission optimization based on the transmitted data quality evaluation value and a preset transmitted data quality threshold. The transmitted data quality evaluation value is used to quantify and evaluate the quality change of the electromagnetic signal data during the transmission process; S4, after transmission optimization, obtaining a data real-time evaluation value based on the collected data quality evaluation value obtained after acquisition optimization, the transmitted data quality evaluation value obtained after transmission optimization, and the transmitted data obtained after transmission optimization, and determining whether to perform real-time optimization based on the data real-time evaluation value and a preset data real-time threshold. The data real-time evaluation value is used to evaluate the real-time performance of the data.

[0010] Further, the specific method for processing the initial electromagnetic signal data of the high-voltage cable obtained by the sensor is as follows: separating the initial electromagnetic signal data to obtain initial signal data and initial noise data, squaring the root mean square of the initial signal data to obtain the initial signal power, and squaring the root mean square of the initial noise data to obtain the initial noise power; statistically analyzing the initial electromagnetic signal data to obtain the initial pulse number and initial pulse amplitude, determining whether the initial pulse amplitude is less than the preset pulse amplitude threshold, if the initial pulse amplitude is not less than the preset pulse amplitude threshold, then recording this pulse as a valid pulse and statistically obtaining the total number of initial valid pulses, otherwise, not recording this pulse as a valid pulse; obtaining the initial maximum time, initial minimum time, and initial valid time period of the initial electromagnetic signal data through the time stamp of the obtained initial electromagnetic signal data, where the initial maximum time represents the acquisition end time of the initial electromagnetic signal data, the initial minimum time represents the acquisition start time of the initial electromagnetic signal data, and the initial valid time period represents the time range covered by the remaining data points after removing the abnormal data points in the initial electromagnetic signal data, and the abnormal data points represent the data points outside the range of the average value of the initial electromagnetic signal data plus or minus three standard deviations; performing frequency domain analysis on the initial electromagnetic signal data through Fourier transform to obtain the initial spectral power density; performing reciprocal operation on the average time difference between the initial sampling points to obtain the initial actual sampling rate, and performing ratio operation on the initial actual sampling rate and the preset sampling rate to obtain the initial sampling rate consistency coefficient, where the initial sampling rate consistency coefficient represents the deviation between the initial actual sampling rate and the preset sampling rate; performing correlation coefficient operation on the obtained initial electromagnetic signal data and the standard waveform to obtain the initial waveform matching degree.

[0011] Further, the specific method for obtaining the acquisition data quality evaluation value is as follows: analyzing the relative relationship between the obtained initial signal power and initial noise power to obtain the initial signal-to-noise ratio; analyzing the relative relationship between the total number of initial valid pulses and the initial pulse number to obtain the initial valid pulse ratio; processing the initial signal-to-noise ratio and the initial valid pulse ratio to obtain the acquisition data effective coefficient, where the acquisition data effective coefficient is used to quantify the effectiveness of the acquired initial electromagnetic signal data; analyzing the relative relationship between the initial maximum time, initial minimum time, and initial valid time period to obtain the initial missing time period ratio; processing the initial sampling rate consistency coefficient and the initial waveform matching degree to obtain the acquisition data consistency coefficient, where the acquisition data consistency coefficient is used to quantify the consistency of the acquired initial electromagnetic signal data; processing the acquisition data effective coefficient, the acquisition data consistency coefficient, and the initial missing time period ratio to obtain the acquisition data quality evaluation value.

[0012] Further, before obtaining the transmission data quality evaluation value by performing transmission evaluation on the initially acquired electromagnetic signal data and the transmitted electromagnetic signal data after acquisition optimization, it also includes analyzing the transmitted electromagnetic signal data to obtain transmission data parameters; the transmission data parameters include the transmitted signal power, the transmitted noise power, the total number of effective pulses after transmission, the number of pulses after transmission, and the spectral power density after transmission; the specific process of obtaining the transmission data parameters is as follows: separating the transmitted electromagnetic signal data to obtain the transmitted signal data and the transmitted noise data, squaring the root mean square of the transmitted signal data to obtain the transmitted signal power; squaring the root mean square of the transmitted noise data to obtain the transmitted noise power; statistically analyzing the transmitted electromagnetic signal data to obtain the number of pulses after transmission and the pulse amplitude after transmission, and determining whether the pulse amplitude after transmission is less than the preset pulse amplitude threshold. If the pulse amplitude after transmission is not less than the preset pulse amplitude threshold, then this pulse is recorded as an effective pulse, and the total number of effective pulses after transmission is statistically obtained, otherwise no operation is performed; performing frequency domain analysis on the transmitted electromagnetic signal data through Fourier transform to obtain the spectral power density after transmission.

[0013] Further, the specific method for obtaining the transmission data quality evaluation value by performing transmission evaluation on the initially acquired electromagnetic signal data and the transmitted electromagnetic signal data after acquisition optimization is as follows: performing a correlation coefficient operation on the initially acquired electromagnetic signal data and the transmitted electromagnetic signal data after acquisition optimization to obtain a data similarity coefficient; analyzing the relative relationship between the initial pulse amplitude and the pulse amplitude after transmission to obtain a pulse amplitude deviation; analyzing the relative relationship between the initial spectral power density and the spectral power density after transmission to obtain a spectral deviation; processing the pulse amplitude deviation and the spectral deviation to obtain a transmission data integrity coefficient; analyzing the relative relationship between the transmitted signal power and the transmitted noise power obtained to obtain the signal-to-noise ratio after transmission, and analyzing the relative relationship between the initial signal-to-noise ratio and the signal-to-noise ratio after transmission to obtain a signal-to-noise ratio deviation; analyzing the relative relationship between the total number of effective pulses after transmission and the number of pulses after transmission to obtain the proportion of effective pulses after transmission, and analyzing the relative relationship between the initial proportion of effective pulses and the proportion of effective pulses after transmission to obtain an effective pulse proportion deviation; processing the signal-to-noise ratio deviation and the effective pulse proportion deviation to obtain a transmission data effectiveness coefficient; processing the acquisition data quality evaluation value, the data similarity coefficient, the transmission data integrity coefficient, and the transmission data effectiveness coefficient to obtain the transmission data quality evaluation value; the specific limiting expression of the transmission data quality evaluation value is:

[0014] ;

[0015] ;

[0016] ;

[0017] ;

[0018] In the formula, i represents the number of the preset time points, T, T represents the total number of the preset time periods, represents the initial electromagnetic signal data at the i-th preset time point, represents the average value of the initial electromagnetic signal data, represents the electromagnetic signal data after transmission at the i-th preset time point, represents the average value of the electromagnetic signal data after transmission, SZL represents the evaluation value of the transmission data quality, represents the evaluation value of the acquisition data quality obtained after acquisition optimization, SXS represents the data similarity coefficient, SQU represents the transmission data integrity coefficient, SYX represents the transmission data effectiveness coefficient, CFU represents the initial pulse amplitude, SFU represents the pulse amplitude after transmission, CPI represents the initial spectral power density, SPI represents the spectral power density after transmission, XHG represents the initial signal power, ZSG represents the initial noise power, YMC represents the total number of initial effective pulses, MSH represents the initial number of pulses, SHG represents the signal power after transmission, SSG represents the noise power after transmission, SMC represents the total number of effective pulses after transmission, and SMH represents the number of pulses after transmission.

[0019] Furthermore, the specific method for obtaining the data real-time evaluation value based on the evaluation value of the acquisition data quality obtained after acquisition optimization, the evaluation value of the transmission data quality obtained after transmission optimization, and the transmission data obtained after transmission optimization is as follows: Obtain the preset transmission data from the preset database, and the preset transmission data includes the preset transmission rate, the preset data transmission delay, and the preset transmission distance; Analyze and obtain the transmission coefficient according to the relative relationship between the transmission data and the preset transmission data, and the transmission coefficient represents the deviation between the transmission data and the preset transmission data, and the transmission data includes the transmission rate, the data transmission delay, and the transmission distance; Process the transmission coefficient, the evaluation value of the acquisition data quality obtained after acquisition optimization, and the evaluation value of the transmission data quality obtained after transmission optimization to obtain the data real-time evaluation value.

[0020] An embodiment of the present application provides an online abnormal monitoring system for high-voltage cables, including: an initial data evaluation module, a data transmission module, a post-transmission data evaluation module, and a data real-time evaluation module; wherein, the initial data evaluation module is used to process and evaluate the initial electromagnetic signal data of the high-voltage cable obtained through sensors to obtain a collected data quality evaluation value, and judge whether to perform acquisition optimization based on the collected data quality evaluation value and a preset collected data quality threshold. The initial electromagnetic signal data represents a set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable, and the collected data quality evaluation value is used to quantify the quality of the collected initial electromagnetic signal data; the data transmission module is used to transmit the initial electromagnetic signal data to the cloud after acquisition optimization, and obtain transmission data and post-transmission electromagnetic signal data. The transmission data represents the transmission information during the data transmission process, and the post-transmission electromagnetic signal data represents the data after the initial electromagnetic signal data is transmitted; the post-transmission data evaluation module is used to perform transmission evaluation based on the initial electromagnetic signal data and the post-transmission electromagnetic signal data obtained after acquisition optimization to obtain a transmission data quality evaluation value, and judge whether to perform transmission optimization based on the transmission data quality evaluation value and a preset transmission data quality threshold. The transmission data quality evaluation value is used to quantify and evaluate the quality change of the electromagnetic signal data during the transmission process; the data real-time evaluation module is used to obtain a data real-time evaluation value based on the collected data quality evaluation value obtained after acquisition optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization, and judge whether to perform real-time optimization based on the data real-time evaluation value and a preset data real-time threshold. The data real-time evaluation value is used to evaluate the real-time performance of the data.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. By obtaining the collected data quality evaluation value from the obtained initial electromagnetic signal data, then obtaining the transmission data quality evaluation value according to the initial electromagnetic signal data and the post-transmission electromagnetic signal data, and finally obtaining the data real-time evaluation value according to the optimized collected data quality evaluation value, transmission data quality evaluation value, and transmission data, the real-time performance of the data is accurately quantified, thereby improving the accuracy of online abnormal monitoring of high-voltage cables and effectively solving the problem of low accuracy of online abnormal monitoring of high-voltage cables in the prior art.

[0023] 2. Obtain the acquisition data effective coefficient based on the acquired initial signal-to-noise ratio and initial effective pulse duty ratio, and analyze the ratio of the initial missing time period based on the relative relationship among the initial maximum time, initial minimum time, and initial effective time period; obtain the acquisition data consistency coefficient from the initial sampling rate consistency coefficient and initial waveform matching degree. Finally, obtain the acquisition data quality evaluation value from the acquisition data effective coefficient, acquisition data consistency coefficient, and ratio of the initial missing time period, thereby quantitatively evaluating the quality of the acquired electromagnetic signal data, and further improving the data accuracy in the on-line abnormal monitoring of high-voltage cables.

[0024] 3. Calculate the data similarity coefficient through the correlation coefficient operation between the initial electromagnetic signal data and the transmitted electromagnetic signal data. Then, obtain the transmission data integrity coefficient from the acquired pulse amplitude deviation and spectrum deviation. Next, obtain the transmission data effective coefficient from the acquired signal-to-noise ratio deviation and effective pulse duty ratio deviation. Finally, obtain the transmission data quality evaluation value from the acquisition data quality evaluation value, data similarity coefficient, transmission data integrity coefficient, and transmission data effective coefficient, thereby comprehensively evaluating the changes in the abnormal monitoring signal of the high-voltage cable during the transmission process, and further detecting potential signal damage, attenuation, or noise interference. Description of the Drawings

[0025] Figure 1 It is a flowchart of a method for on-line abnormal monitoring of high-voltage cables provided by an embodiment of the present application;

[0026] Figure 2 It is a schematic diagram showing the change of the transmission coefficient with the change of the transmission rate provided by an embodiment of the present application;

[0027] Figure 3 It is a schematic diagram showing the change of the transmission coefficient with the change of the data transmission delay provided by an embodiment of the present application;

[0028] Figure 4 It is a schematic diagram showing the change of the transmission coefficient with the change of the transmission distance provided by an embodiment of the present application;

[0029] Figure 5 It is a schematic structural diagram of an on-line abnormal monitoring system for high-voltage cables provided by an embodiment of the present application. Detailed Embodiments

[0030] Embodiments of the present application provide a method and system for on-line abnormal monitoring of high-voltage cables, which solve the problem of low accuracy of on-line abnormal monitoring of high-voltage cables in the prior art. By processing and evaluating the obtained initial electromagnetic signal data of the high-voltage cable, a collection data quality evaluation value is obtained. If it is less than a preset collection data quality threshold, collection optimization is performed. Then, according to the obtained initial electromagnetic signal data and the transmitted electromagnetic signal data, a transmission data quality evaluation value is obtained. If it is less than a preset transmission data quality threshold, transmission optimization is performed. Finally, according to the collection data quality evaluation value obtained after collection optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data, a data real-time evaluation value is obtained. If it is less than a preset data real-time evaluation threshold, real-time optimization is performed, achieving an improvement in the accuracy of on-line abnormal monitoring of high-voltage cables.

[0031] The technical solution in the embodiments of the present application is to solve the problem of low accuracy of on-line abnormal monitoring of the above high-voltage cables. The general idea is as follows:

[0032] A collection data quality evaluation value is obtained through the obtained initial electromagnetic signal data. If it is less than a preset collection data quality threshold, collection is optimized. Then, a transmission data quality evaluation value is obtained according to the initial electromagnetic signal data and the transmitted electromagnetic signal data. If it is less than a preset transmission data quality threshold, transmission is optimized. Finally, a data real-time evaluation value is obtained according to the optimized collection data quality evaluation value, transmission data quality evaluation value, and transmission data. If it is less than a preset data real-time evaluation threshold, real-time performance is optimized, achieving the effect of improving the accuracy of on-line abnormal monitoring of high-voltage cables.

[0033] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific implementation manners.

[0034] Such as Figure 1As shown in the figure, it is a flowchart of a method for on-line abnormal monitoring of high-voltage cables provided by an embodiment of the present application. The method includes the following steps: S1, Initial data evaluation: Process and evaluate the initial electromagnetic signal data of the high-voltage cable obtained by the sensor to obtain a collection data quality evaluation value. Determine whether to perform collection optimization based on the collection data quality evaluation value and a preset collection data quality threshold. The initial electromagnetic signal data represents a set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable. The collection data quality evaluation value is used to quantify the quality of the collected initial electromagnetic signal data; S2, Data transmission: After collection optimization, transmit the initial electromagnetic signal data to the cloud, and obtain transmission data and post-transmission electromagnetic signal data. The transmission data represents the transmission information during the data transmission process. The post-transmission electromagnetic signal data represents the data after the initial electromagnetic signal data is transmitted; S3, Post-transmission data evaluation: Perform transmission evaluation based on the initial electromagnetic signal data and the post-transmission electromagnetic signal data obtained after collection optimization to obtain a transmission data quality evaluation value. Determine whether to perform transmission optimization based on the transmission data quality evaluation value and a preset transmission data quality threshold. The transmission data quality evaluation value is used to quantify and evaluate the quality change of the electromagnetic signal data during the transmission process; S4, Data real-time evaluation: After transmission optimization, obtain a data real-time evaluation value based on the collection data quality evaluation value obtained after collection optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization. Determine whether to perform real-time optimization based on the data real-time evaluation value and a preset data real-time threshold. The data real-time evaluation value is used to evaluate the real-time nature of the data.

[0035] In this embodiment, the cloud represents the data receiving end; the sensor is a high-frequency current sensor, usually installed outside the shielding layer of the high-voltage cable and arranged at key nodes of the cable (such as cable joints, terminals, connection points); the number of sensors is set according to the length and installation environment of the cable. The total number of sensors corresponding to a common high-voltage cable monitoring system may be between 5 and 20. For a 100-meter-long high-voltage cable, one sensor is arranged every 20 - 30 meters on average; through collection optimization, transmission optimization, and real-time optimization, the loss and error of data during collection and transmission can be minimized to the greatest extent, and the reliability and timeliness of the data can be improved; through the above steps, the accuracy of on-line abnormal monitoring of high-voltage cables is improved, which is conducive to timely discovery and handling of abnormal conditions of high-voltage cables.

[0036] It should be added that the specific method for processing the initial electromagnetic signal data of the high-voltage cable obtained through the sensor is as follows: The initial electromagnetic signal data is separated into initial signal data and initial noise data. The root mean square of the initial signal data is squared to obtain the initial signal power, and the root mean square of the initial noise data is squared to obtain the initial noise power; The initial electromagnetic signal data is statistically analyzed to obtain the initial pulse number and the initial pulse amplitude. It is judged whether the initial pulse amplitude is less than the preset pulse amplitude threshold. If the initial pulse amplitude is not less than the preset pulse amplitude threshold, this pulse is recorded as a valid pulse, and the total number of initial valid pulses is statistically obtained. Otherwise, this pulse is not recorded as a valid pulse; The initial maximum time, the initial minimum time, and the initial valid time period of the initial electromagnetic signal data are obtained through the time stamp of the acquired initial electromagnetic signal data. The initial maximum time represents the end time of the acquisition of the initial electromagnetic signal data, the initial minimum time represents the start time of the acquisition of the initial electromagnetic signal data, and the initial valid time period represents the time range covered by the remaining data points after removing the abnormal data points in the initial electromagnetic signal data. The abnormal data points represent the data points outside the range of the average value of the initial electromagnetic signal data plus or minus three standard deviations; The initial electromagnetic signal data is subjected to frequency domain analysis through Fourier transform to obtain the initial spectral power density; The reciprocal operation is performed through the average time difference between the initial sampling points to obtain the initial actual sampling rate. The ratio operation is performed between the initial actual sampling rate and the preset sampling rate to obtain the initial sampling rate consistency coefficient, and the initial sampling rate consistency coefficient represents the deviation between the initial actual sampling rate and the preset sampling rate; The correlation coefficient operation is performed between the acquired initial electromagnetic signal data and the standard waveform to obtain the initial waveform matching degree.

[0037] It should be understood that in electromagnetic signal processing, the blind source separation technology is used to separate the initial signal data and the initial noise data from the initial electromagnetic signal data. Independent Component Analysis (ICA) is a commonly used method of the blind source separation technology.

[0038] The initial noise data represents the interference signal of the cable surrounding environment or the measuring device; the initial signal data represents the signal directly related to the cable state; the initial signal power is used to measure the initial signal strength; the initial noise power is used to measure the influence of the initial noise; the preset pulse amplitude threshold is represented by the maximum value of the pulse amplitude within the historical time period; the historical time period is set from the beginning of last month to the beginning of this month. For example, if the current date is August 11th, the historical time period is set from July 1st to August 1st; count the number of pulses in the initial electromagnetic signal and judge the amplitude of each pulse. If the pulse amplitude is higher than the preset pulse amplitude threshold, it is regarded as a valid pulse; the preset sampling rate is set according to the Nyquist sampling theorem. For example, if the signal frequency range is from 1 kHz to 10 kHz, the sampling rate is at least twice the highest frequency of the signal, that is, 20 kHz; the initial waveform matching degree represents the matching degree between the waveform of the initial electromagnetic signal data and the standard waveform; the standard waveform is obtained by performing feature analysis on the initial electromagnetic signal data within the historical time period; separating the initial signal data and the initial noise data helps to further analyze and process the signal, reduce noise interference, and improve the effectiveness of the signal; obtaining the initial signal power and the initial noise power is beneficial to evaluating the quality of the signal; the statistical number of valid pulses reflects the key events in the electromagnetic signal (such as faults or abnormal currents in high-voltage cables); by means of various analysis methods (such as Fourier transform, sampling rate analysis, waveform matching, etc.), the characteristics and quality of the signal are obtained, so as to quantify the real-time performance and accuracy of the data, and then the health status monitoring of the high-voltage cable and the identification of potential faults or abnormalities are realized.

[0039] Further, the specific method for obtaining the acquisition data quality evaluation value is as follows: analyze the relative relationship between the obtained initial signal power and the initial noise power to obtain the initial signal-to-noise ratio (i.e., in the specific limit expression of the acquisition data quality evaluation value); analyze the relative relationship between the total number of initial valid pulses and the number of initial pulses to obtain the initial valid pulse ratio (i.e., ); Process the initial signal-to-noise ratio and the initial effective pulse duty ratio to obtain the acquisition data effectiveness coefficient (i.e., CYX in the specific limit expression of the acquisition data quality evaluation value), and the acquisition data effectiveness coefficient is used to quantify the effectiveness of the initially acquired electromagnetic signal data; Analyze the relative relationship among the initial maximum time, the initial minimum time, and the initial effective time period to obtain the proportion of the initial missing time period (i.e., QSJ in the specific limit expression of the acquisition data quality evaluation value); Process the initial sampling rate consistency coefficient and the initial waveform matching degree to obtain the acquisition data consistency coefficient (i.e., CYZ in the specific limit expression of the acquisition data quality evaluation value), and the acquisition data consistency coefficient is used to quantify the consistency of the initially acquired electromagnetic signal data; Process the acquisition data effectiveness coefficient, the acquisition data consistency coefficient, and the proportion of the initial missing time period to obtain the acquisition data quality evaluation value.

[0040] Among them, the specific limit expression of the acquisition data quality evaluation value is:

[0041] ;

[0042] ;

[0043] ;

[0044] ;

[0045] In the formula, CJZ represents the acquisition data quality evaluation value, CYX represents the acquisition data effectiveness coefficient, CYZ represents the acquisition data consistency coefficient, QSJ represents the proportion of the initial missing time period, XHG represents the initial signal power, ZSG represents the initial noise power, YMC represents the total number of initial effective pulses, MSH represents the initial number of pulses, CLV represents the initial sampling rate consistency coefficient, BOX represents the initial waveform matching degree, MAS represents the initial maximum time, MIS represents the initial minimum time, and YUS represents the initial effective time period.

[0046] In this embodiment, the signal-to-noise ratio represents the ratio of the signal power to the noise power and is used to measure the signal quality; the effective pulse represents the pulse that can be regarded as effective information in signal processing; the initial effective pulse ratio represents the ratio of the number of initial effective pulses to the number of initial pulses and is used to measure the effectiveness of the pulse signal; the initial missing time period ratio represents the ratio of the time period of abnormal data points to the total time period and is used to evaluate the degree of data missing; the time unit is uniformly seconds. For example, data is collected from 10:00:00 to 10:10:00, that is, the initial minimum time is 10:00:00 and the initial maximum time is 10:10:00, then the total collection time period is 600 seconds. If the initial effective time period is 550 seconds, then the missing time period is 50 seconds; by comprehensively considering multiple aspects such as the effectiveness, consistency, and missing degree of the data, a quantitative evaluation of the quality of the collected electromagnetic signal data is achieved.

[0047] The missing time period may lead to inconsistent sampling rates (because sampling cannot be performed during the missing time period), thereby affecting the initial sampling rate consistency coefficient. The missing time period may also lead to an incomplete waveform, affecting the initial waveform matching degree. The longer the missing time period, the smaller the evaluation value of the collected data quality.

[0048] Inconsistent sampling rates may lead to waveform mismatches (because waveforms at different sampling rates may be different), thereby affecting the initial waveform matching degree. Inconsistent sampling rates may also affect the signal-to-noise ratio (because the noise levels at different sampling rates may be different), thereby affecting the initial signal-to-noise ratio. The larger the initial sampling rate consistency coefficient, the larger the evaluation value of the collected data quality.

[0049] The waveform matching degree may affect the signal-to-noise ratio (because waveform mismatches may lead to the introduction or amplification of noise), thereby affecting the initial signal-to-noise ratio. The larger the initial waveform matching degree, the larger the evaluation value of the collected data quality.

[0050] The signal-to-noise ratio also reflects the accuracy of the data, thereby affecting the data quality evaluation value. The larger the initial signal-to-noise ratio, the better the quality of the signal, the smaller the interference of the noise, and the larger the evaluation value of the collected data quality.

[0051] The effective pulse ratio is related to the integrity, accuracy, etc. of the data. For example, the missing time period may lead to a reduction in effective pulses, inconsistent sampling rates may lead to distortion or loss of pulses; waveform mismatches may lead to misjudgment of pulses, etc. The higher the initial effective pulse ratio, the more useful information in the data, and the larger the evaluation value of the collected data quality.

[0052] The evaluation value of the collected data quality is used to quantify the quality of the collected initial electromagnetic signal data. The larger the evaluation value of the collected data quality, the better the quality of the initial electromagnetic signal data.

[0053] Further, the specific steps for determining whether to perform acquisition optimization based on the acquired data quality evaluation value and the preset acquired data quality threshold are as follows: A1. Determine whether the acquired data quality evaluation value is less than the preset acquired data quality threshold. If the acquired data quality evaluation value is less than the preset acquired data quality threshold, then execute A2; otherwise, do not perform acquisition optimization. A2. Perform signal processing optimization, and at the same time determine whether the acquired data quality evaluation value monitored after the signal processing optimization is less than the preset acquired data quality threshold. If so, then execute A3; otherwise, end the acquisition optimization. The signal processing optimization includes removing background noise and data smoothing. A3. Adjust the sampling rate, and at the same time determine whether the acquired data quality evaluation value obtained after the sampling rate adjustment is less than the preset acquired data quality threshold. If so, then execute A4; otherwise, end the acquisition optimization. The minimum sampling rate is set according to the electromagnetic signal frequency. A4. Re-acquire the initial electromagnetic signal data, and determine whether the acquired data quality evaluation value obtained after the re-acquisition is less than the preset acquired data quality threshold. If the acquired data quality evaluation value obtained after the re-acquisition is less than the preset acquired data quality threshold, then give feedback; otherwise, end the acquisition optimization.

[0054] In this embodiment, the preset acquired data quality threshold is obtained from a preset database and set by the average value of the acquired data quality evaluation values within a historical time period; send a first feedback report to a preset person; the first feedback report includes the data quality evaluation value, the acquired data quality evaluation value monitored after the signal processing optimization, the acquired data quality evaluation value obtained after the sampling rate adjustment, and the acquired data quality evaluation value obtained after the re-acquisition; remove background noise by applying a selected filter to the acquired initial electromagnetic signal data. The filter is selected according to the frequency characteristics of the background noise. For example, if the main frequency of the initial signal data is below 50 kHz and the initial noise data is concentrated above 100 kHz, a low-pass filter with a cut-off frequency of about 50 kHz is selected at this time, so that the discharge signal below 50 kHz passes through while attenuating the noise above 100 kHz; apply a selected smoothing method to the acquired initial electromagnetic signal data. The smoothing method is selected according to the characteristics and requirements of the signal. For example, spline interpolation is suitable for scenarios where a high degree of smoothing needs to be achieved with a small number of points.

[0055] The preset sampling rate is set according to the Nyquist sampling theorem; determine whether the actual sampling rate is less than the preset sampling rate. If so, increase the actual sampling rate to the preset sampling rate; otherwise, reduce the actual sampling rate to the preset sampling rate. After adjusting the sampling rate, re-acquire the initial electromagnetic signal and evaluate the acquired data quality evaluation value. If the acquired data quality evaluation value after the adjustment is less than the preset acquired data quality threshold, the sampling rate can be further fine-tuned and the verification process can be repeated until the optimal sampling rate setting is found.

[0056] In this embodiment, through operations such as signal processing optimization, sampling rate adjustment, and re - acquisition, the data quality is gradually improved to meet the threshold requirements, ensuring data transmission or processing for high - voltage cable anomaly monitoring based on high - quality data, thereby achieving an improvement in the accuracy and reliability of high - voltage cable anomaly monitoring.

[0057] Furthermore, a transmission data quality evaluation value is obtained based on the initial electromagnetic signal data and the transmitted electromagnetic signal data after acquisition optimization. Before that, it also includes analyzing the transmitted electromagnetic signal data to obtain transmission data parameters; the transmission data parameters include transmitted signal power, transmitted noise power, total number of transmitted effective pulses, number of transmitted pulses, and transmitted spectral power density; the specific process of obtaining the transmission data parameters is as follows: separating the transmitted electromagnetic signal data into transmitted signal data and transmitted noise data, squaring the root - mean - square of the transmitted signal data to obtain the transmitted signal power; squaring the root - mean - square of the transmitted noise data to obtain the transmitted noise power; counting the number of transmitted pulses and the transmitted pulse amplitude in the transmitted electromagnetic signal data, and determining whether the transmitted pulse amplitude is less than a preset pulse amplitude threshold. If the transmitted pulse amplitude is not less than the preset pulse amplitude threshold, then this pulse is recorded as an effective pulse, and the total number of transmitted effective pulses is counted, otherwise no operation is performed; performing frequency - domain analysis on the transmitted electromagnetic signal data through Fourier transform to obtain the transmitted spectral power density.

[0058] In this embodiment, the independent component analysis method is used to separate the transmitted signal data and the transmitted noise data from the transmitted electromagnetic signal data; the transmitted noise data represents the interference signal of the cable surrounding environment or measurement equipment; the transmitted signal data represents the signal directly related to the cable state; the transmitted signal power is used to measure the transmitted signal strength; the transmitted noise power is used to measure the influence of the transmitted noise; obtaining the transmitted frequency - domain signal by performing a fast Fourier transform on the transmitted electromagnetic signal data, squaring the absolute value of the transmitted frequency - domain signal to obtain the transmitted power spectrum, dividing the sampling frequency of the transmitted electromagnetic signal data by the number of sampling points to obtain the transmitted frequency resolution, and dividing the transmitted power spectrum by the transmitted frequency resolution to obtain the transmitted power spectral density; through the above steps, a comprehensive evaluation of the signal loss during the transmission process of on - line anomaly monitoring of high - voltage cables is achieved, providing strong support for the monitoring and fault detection of high - voltage cable anomaly monitoring.

[0059] Furthermore, the specific method for obtaining the transmission data quality evaluation value by performing transmission evaluation based on the initial electromagnetic signal data and the transmitted electromagnetic signal data after acquisition optimization is as follows: Perform a correlation coefficient operation on the initial electromagnetic signal data obtained after acquisition optimization and the transmitted electromagnetic signal data to obtain a data similarity coefficient (i.e., SXS in the specific limit expression of the transmission data quality evaluation value). The data similarity coefficient represents the similarity degree between the initial electromagnetic signal data and the transmitted electromagnetic signal data; Analyze the relative relationship between the initial pulse amplitude and the transmitted pulse amplitude to obtain a pulse amplitude deviation (i.e., in the specific limit expression of the transmission data quality evaluation value). The pulse amplitude deviation represents the deviation between the initial pulse amplitude and the transmitted pulse amplitude; Analyze the relative relationship between the initial spectral power density and the transmitted spectral power density to obtain a spectral deviation (i.e., in the specific limit expression of the transmission data quality evaluation value). The spectral deviation represents the deviation between the initial spectral power density and the transmitted spectral power density; Process the pulse amplitude deviation and the spectral deviation to obtain a transmission data integrity coefficient (i.e., SQU in the specific limit expression of the transmission data quality evaluation value). The transmission data integrity coefficient is used to quantify the integrity degree of the transmitted electromagnetic signal data; Analyze the relative relationship between the obtained transmitted signal power and the transmitted noise power to obtain the transmitted signal-to-noise ratio (i.e., in the specific limit expression of the transmission data quality evaluation value). Analyze the relative relationship between the initial signal-to-noise ratio and the transmitted signal-to-noise ratio to obtain a signal-to-noise ratio deviation (i.e., in the specific limit expression of the transmission data quality evaluation value). The signal-to-noise ratio deviation represents the deviation between the initial signal-to-noise ratio and the transmitted signal-to-noise ratio; Analyze the relative relationship between the total number of effective pulses after transmission and the number of pulses after transmission to obtain the proportion of effective pulses after transmission (i.e., in the specific limit expression of the transmission data quality evaluation value). Analyze the relative relationship between the proportion of effective pulses initially and the proportion of effective pulses after transmission to obtain a deviation in the proportion of effective pulses (i.e., in the specific limit expression of the transmission data quality evaluation value). The deviation in the proportion of effective pulses represents the deviation between the initial proportion of effective pulses and the proportion of effective pulses after transmission; Process the signal-to-noise ratio deviation and the deviation in the proportion of effective pulses to obtain a transmission data effectiveness coefficient (i.e., SYX in the specific limit expression of the transmission data quality evaluation value). The transmission data effectiveness coefficient is used to quantify the effectiveness of the transmitted electromagnetic signal data; Process the acquisition data quality evaluation value, the data similarity coefficient, the transmission data integrity coefficient, and the transmission data effectiveness coefficient to obtain the transmission data quality evaluation value; The specific limit expression of the transmission data quality evaluation value is:

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] In the formula, i represents the number of the preset time point, T, T represents the total number of the preset time periods, represents the initial electromagnetic signal data of the i-th preset time point, represents the average value of the initial electromagnetic signal data, represents the electromagnetic signal data after transmission of the i-th preset time point, represents the average value of the electromagnetic signal data after transmission, SZL represents the transmission data quality evaluation value, represents the acquisition data quality evaluation value obtained after acquisition optimization, SXS represents the data similarity coefficient, SQU represents the transmission data integrity coefficient, SYX represents the transmission data validity coefficient, CFU represents the initial pulse amplitude, SFU represents the pulse amplitude after transmission, CPI represents the initial spectral power density, SPI represents the spectral power density after transmission, XHG represents the initial signal power, ZSG represents the initial noise power, YMC represents the total number of initial effective pulses, MSH represents the initial number of pulses, SHG represents the signal power after transmission, SSG represents the noise power after transmission, SMC represents the total number of effective pulses after transmission, and SMH represents the number of pulses after transmission.

[0065] In this embodiment, the data similarity coefficient reflects the similarity between the initial electromagnetic signal data and the electromagnetic signal data after transmission, and its value range is [-1, 1]. The closer the data similarity coefficient is to 1, the higher the similarity of the two groups of data. The higher the data similarity coefficient, the more consistent the signal characteristics are, which means that the pulse amplitude deviation, spectral deviation, etc. are also lower. The higher the data similarity coefficient, usually the smaller the distortion or deviation that occurs during signal transmission, so it has a positive impact on the transmission data quality evaluation value, and the larger the transmission data quality evaluation value;

[0066] The pulse amplitude deviation reflects the change in intensity after signal transmission. The smaller the deviation, the smaller the change in signal intensity, and the larger the transmission data integrity coefficient. The smaller the pulse amplitude deviation, the smaller the change in the overall shape and characteristics of the signal, and thus the higher the data similarity coefficient. Therefore, the smaller the pulse amplitude deviation, the larger the transmission data quality evaluation value.

[0067] The spectral deviation is used to reflect whether the frequency components of the signal change during transmission. The spectral deviation is closely related to the signal morphology. Therefore, when the spectral deviation is small, the data similarity coefficient will also be high. The smaller the spectral deviation, the smaller the power change of the signal at different frequencies, indicating that the spectral information of the signal has not changed significantly and the transmission data integrity coefficient is higher. Therefore, the smaller the spectral deviation, the larger the transmission data quality evaluation value.

[0068] The smaller the deviation of the signal-to-noise ratio, the less signal attenuation or noise interference in the transmission process. A small signal-to-noise ratio deviation indicates that the change of the signal relative to the noise is small, the interference and attenuation of the signal in the transmission process are less, and the transmission data effectiveness coefficient is also higher. A small signal-to-noise ratio deviation often means less noise interference to the signal, and the deviation of the effective pulse ratio will also be small. Therefore, the smaller the signal-to-noise ratio deviation, the larger the transmission data quality evaluation value.

[0069] The deviation of the effective pulse ratio reflects whether the effective signal decreases during transmission. A smaller deviation of the effective pulse ratio indicates that the effective signal is not significantly affected during transmission, and the transmission data effectiveness coefficient is higher. Therefore, the smaller the deviation of the effective pulse ratio, the larger the transmission data quality evaluation value.

[0070] When the data similarity coefficient is higher and each deviation is smaller, the transmission data quality evaluation value is higher, indicating that the signal for on-line abnormal monitoring of high-voltage cables maintains good quality during transmission.

[0071] Through data analysis in multiple aspects, including the correlation coefficient, amplitude deviation, spectral deviation, signal-to-noise ratio, and effective pulse ratio, etc., a comprehensive evaluation of the changes in the data for on-line abnormal monitoring of high-voltage cables during transmission is achieved, and then the detection of potential signal damage, attenuation, or noise interference is realized.

[0072] The statistical table of the changes in the transmission data quality evaluation value is shown in Table 1:

[0073] Table 1 Statistical table of the changes in the transmission data quality evaluation value

[0074]

[0075] It can be seen from the first group and the second group of data in Table 1 that the transmission data quality evaluation value increases with the increase of the transmission data effectiveness coefficient. It can be seen from the second group and the third group of data that the transmission data quality evaluation value increases with the increase of the transmission data integrity coefficient. It can be seen from the third group and the fourth group of data that the transmission data quality evaluation value increases with the increase of the data similarity coefficient. It can be seen from the fourth group and the fifth group of data that the transmission data quality evaluation value increases with the increase of the collected data quality evaluation value. Therefore, the transmission data quality evaluation value is positively correlated with the transmission data effectiveness coefficient, the transmission data integrity coefficient, the data similarity coefficient, and the collected data quality evaluation value.

[0076] Furthermore, the specific process of determining whether to perform transmission optimization based on the transmission data quality evaluation value and the preset transmission data quality threshold is as follows: B1, determine whether the transmission data quality evaluation value is less than the preset transmission data quality threshold. If the transmission data quality evaluation value is less than the preset transmission data quality threshold, execute B2; otherwise, no transmission optimization is performed. B2, perform packet loss compensation, and determine whether the transmission data quality evaluation value obtained after packet loss compensation is less than the preset transmission data quality threshold. If so, execute B3; otherwise, end the transmission optimization. B3, send an automatic repeat request to recover data loss, and determine whether the transmission data quality evaluation value obtained after retransmission is less than the preset transmission data quality threshold. If the transmission data quality evaluation value obtained after retransmission is less than the preset transmission data quality threshold, execute B4; otherwise, end the transmission optimization. B4, perform encryption integrity verification, and determine whether the transmission data quality evaluation value obtained after encryption integrity verification is less than the preset transmission data quality threshold. If so, give feedback; otherwise, end the transmission optimization.

[0077] In this embodiment, the preset transmission data quality threshold is represented by the maximum value of the transmission data quality evaluation values within the historical time period; a second feedback report is sent to the preset personnel; the second feedback report includes the transmission data quality evaluation value, the transmission data quality evaluation value obtained after packet compensation, and the transmission data quality evaluation value obtained after retransmission; packet loss compensation recovers the packets through linear interpolation technology; if the transmission data quality evaluation value after packet loss compensation is less than the preset transmission data quality threshold, enter the Automatic Repeat Request (ARQ) stage, send an ARQ signal to the sending end to request the retransmission of the lost or incorrect packets, and after receiving the ARQ signal, the sending end retransmits the requested packets.

[0078] Encryption integrity verification is achieved by adding an encrypted hash value to the transmission data, and the receiving end uses the same hash algorithm and key to verify whether the received data is complete and has not been tampered with; by gradually applying packet loss compensation, automatic repeat request, and encryption integrity verification, errors and losses in the data transmission process of on-line abnormal monitoring of high-voltage cables are detected and corrected, thereby improving the reliability and accuracy of data transmission in on-line abnormal monitoring of high-voltage cables.

[0079] Further, the specific method for obtaining the real-time data evaluation value based on the acquisition data quality evaluation value obtained after acquisition optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization is as follows: Obtain preset transmission data from a preset database, where the preset transmission data includes a preset transmission rate, a preset data transmission delay, and a preset transmission distance; Analyze the transmission coefficient (i.e., SXS in the specific limit expression of the real-time data evaluation value) based on the relative relationship between the transmission data and the preset transmission data, and the transmission coefficient represents the deviation between the transmission data and the preset transmission data. The transmission data includes the transmission rate, the data transmission delay, and the transmission distance; Process the transmission coefficient, the acquisition data quality evaluation value obtained after acquisition optimization, and the transmission data quality evaluation value obtained after transmission optimization to obtain the real-time data evaluation value.

[0080] Among them, the specific limit expression of the real-time data evaluation value is:

[0081] ;

[0082] ;

[0083] In the formula, SH represents the real-time data evaluation value, represents the transmission data quality evaluation value obtained after transmission optimization, represents the acquisition data quality evaluation value obtained after acquisition optimization, CAN represents the transmission coefficient, SU represents the transmission rate, represents the preset transmission rate, YAN represents the data transmission delay, represents the preset data transmission delay, JUL represents the transmission distance, represents the preset transmission distance.

[0084] In this embodiment, the preset transmission data is obtained from a preset database. The preset transmission rate is set according to the type of monitoring data. For example, in partial discharge detection, the preset transmission rate is set to 10 Mbps; the preset data transmission delay is set to 10 ms; the preset transmission distance is set to 50 km; Through the above steps, the quantitative evaluation of data quality and transmission efficiency is realized; The real-time data evaluation value comprehensively considers the data quality of the collected data, the data quality after transmission, and the difference between the actual transmission situation and the preset situation, and more comprehensively reflects the overall situation of the data in the on-line abnormal monitoring of high-voltage cables.

[0085] The real-time evaluation value of data is closely related to the transmission rate. The higher the transmission rate, the shorter the data transmission time, thus improving the real-time performance of data. The greater the real-time evaluation value of data, the higher the data real-time performance. Data transmission delay is a key factor affecting data real-time performance. The smaller the data transmission delay, the higher the data real-time performance, and the greater the real-time evaluation value of data. A long transmission delay may cause errors or loss of data during transmission, thus reducing the evaluation value of the transmitted data quality, and further leading to a decrease in the real-time evaluation value of data. The quality of the collected data is the basis of the transmitted data quality. The smaller the evaluation value of the collected data quality, the smaller the evaluation value of the transmitted data quality, and the smaller the real-time evaluation value of data. If a lower transmission rate leads to a longer data transmission delay, it may cause the collected data to fail to reach the receiving end in time for processing, thus affecting the timeliness and accuracy of the data, and further leading to a smaller real-time evaluation value of data. The transmission distance may affect the attenuation of the signal and the degree of noise interference, and thus affect the evaluation result of the collected data quality. The longer the transmission distance, the smaller the evaluation value of the collected data quality may be. As the transmission distance increases, the attenuation of the signal and the noise interference may gradually intensify, resulting in a decrease in the transmission rate and a smaller real-time evaluation value of data.

[0086] Taking the transmission rate between 1 - 50 Mbps, the data transmission delay between 5 - 15 ms, and the transmission distance between 45 - 55 km as an example, with the preset transmission rate of 10 Mbps, the preset data transmission delay of 10 ms, and the preset transmission distance of 50 km, as Figure 2 shown, it is a schematic diagram of the change of the transmission coefficient with the change of the transmission rate provided by the embodiment of the present application. When the data transmission delay is 10 ms and the transmission distance is 50 km, the transmission coefficient increases with the increase of the transmission rate. As Figure 3 shown, it is a schematic diagram of the change of the transmission coefficient with the change of the data transmission delay provided by the embodiment of the present application. When the transmission rate is 10 Mbps and the transmission distance is 50 km, the transmission coefficient decreases with the increase of the data transmission delay. As Figure 4 shown, it is a schematic diagram of the change of the transmission coefficient with the change of the transmission distance provided by the embodiment of the present application. When the transmission rate is 10 Mbps and the data transmission delay is 10 ms, the transmission coefficient decreases with the increase of the transmission distance. Therefore, the transmission coefficient is positively correlated with the transmission rate, and negatively correlated with the data transmission delay and the transmission distance.

[0087] Further, the specific process for determining whether to perform real-time optimization based on the real-time data evaluation value and the preset real-time data evaluation threshold is as follows: C1, determine whether the real-time data evaluation value is less than the preset real-time data evaluation threshold. If the real-time data evaluation value is less than the preset real-time data evaluation threshold, then execute C2; otherwise, do not perform real-time optimization. C2, perform traffic shaping, and determine whether the real-time data evaluation value obtained after traffic shaping is less than the preset real-time data evaluation threshold. If so, then execute C3; otherwise, end the real-time optimization. C3, perform data compression, and determine whether the real-time data evaluation value obtained after data compression is less than the preset real-time data evaluation threshold. If so, then execute C4; otherwise, end the real-time optimization. C4, perform path optimization through multi-path transmission technology, and determine whether the real-time data evaluation value obtained after path optimization is less than the preset real-time data evaluation threshold. If so, then give feedback; otherwise, end the real-time optimization.

[0088] In this embodiment, the preset real-time data evaluation threshold is represented by the maximum value of the real-time data evaluation values within the historical time period; send a third feedback report to the preset personnel; the third feedback report includes the real-time data evaluation value, the real-time data evaluation value obtained after traffic shaping, the real-time data evaluation value obtained after data compression, and the real-time data evaluation value obtained after path optimization.

[0089] Traffic shaping means restricting the transmission rate of traffic through the leaky bucket algorithm, so that the data traffic remains stable within a certain period of time, avoiding network congestion or latency caused by excessive data traffic.

[0090] Data compression technologies include lossy compression and lossless compression. In this embodiment, lossless compression technology is selected; the initial electromagnetic signal data is compressed through the lossless compression algorithm to improve the data transmission efficiency; multi-path transmission means dispersing the data to each communication path through multi-path transmission technology.

[0091] The multi-path transmission control protocol is a standard protocol that supports multi-path data transmission. It can use multiple network interfaces (such as Wi-Fi, 4G, 5G) to transmit data simultaneously. The common default number of paths is between 2 and 4; in this embodiment, the number of communication paths is set to 4.

[0092] Through real-time optimization measures (traffic shaping, data compression, multi-path transmission technology), the data transmission and processing methods are dynamically adjusted and optimized, thereby improving the real-time performance of the data in the on-line abnormal monitoring of high-voltage cables, and further realizing the stability and reliability of the on-line abnormal monitoring of high-voltage cables.

[0093] Such as Figure 5As shown in the figure, it is a schematic structural diagram of an on-line abnormal monitoring system for high-voltage cables provided by an embodiment of the present application. The on-line abnormal monitoring system for high-voltage cables provided by an embodiment of the present application includes: an initial data evaluation module, a data transmission module, a post-transmission data evaluation module, and a data real-time evaluation module; among them, the initial data evaluation module is used to process and evaluate the initial electromagnetic signal data of the high-voltage cable obtained through sensors to obtain a collected data quality evaluation value, and judge whether to perform acquisition optimization based on the collected data quality evaluation value and a preset collected data quality threshold. The initial electromagnetic signal data represents a set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable, and the collected data quality evaluation value is used to quantify the quality of the collected initial electromagnetic signal data; the data transmission module is used to transmit the initial electromagnetic signal data to the cloud after acquisition optimization, and obtain transmission data and post-transmission electromagnetic signal data. The transmission data represents the transmission information during the data transmission process, and the post-transmission electromagnetic signal data represents the data after the initial electromagnetic signal data is transmitted; the post-transmission data evaluation module is used to perform transmission evaluation based on the initial electromagnetic signal data and the post-transmission electromagnetic signal data obtained after acquisition optimization to obtain a transmission data quality evaluation value, and judge whether to perform transmission optimization based on the transmission data quality evaluation value and a preset transmission data quality threshold. The transmission data quality evaluation value is used to quantify and evaluate the quality change of the electromagnetic signal data during the transmission process; the data real-time evaluation module is used to obtain a data real-time evaluation value based on the collected data quality evaluation value obtained after acquisition optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization after transmission optimization, and judge whether to perform real-time optimization based on the data real-time evaluation value and a preset data real-time threshold. The data real-time evaluation value is used to evaluate the real-time performance of the data.

[0094] In this embodiment, by obtaining the initial electromagnetic signal data of the high-voltage cable through sensors and evaluating the quality of the data, the integrity and accuracy of the data in the on-line abnormal monitoring system for high-voltage cables are improved; by comparing the electromagnetic signal data before and after transmission, the consistency between the transmitted data and the initial data is ensured, and the continuity and accuracy of the data in the on-line abnormal monitoring system for high-voltage cables are improved; by combining the collected data quality evaluation value, the transmission data quality evaluation value, and the transmission data, the real-time performance of the entire system is evaluated, thereby improving the real-time performance of the on-line abnormal monitoring system for high-voltage cables, and the accuracy of the on-line abnormal monitoring of high-voltage cables is improved.

[0095] In summary, in the embodiments of the present application, the acquisition data quality evaluation value is obtained from the acquired initial electromagnetic signal data, then the transmission data quality evaluation value is obtained based on the initial electromagnetic signal data and the transmitted electromagnetic signal data, and finally the data real-time evaluation value is obtained according to the optimized acquisition data quality evaluation value, transmission data quality evaluation value, and transmitted data, thereby accurately quantifying the real-time nature of the data, further improving the accuracy of on-line abnormal monitoring of high-voltage cables, and effectively solving the problem of low accuracy of on-line abnormal monitoring of high-voltage cables in the prior art.

[0096] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, system, or computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0098] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0100] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0101] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An on-line abnormal monitoring method for high-voltage cables, characterized in that, It includes the following steps: S1. Process and evaluate the initial electromagnetic signal data of the high-voltage cable obtained by the sensor to obtain the acquisition data quality evaluation value, and judge whether to perform acquisition optimization based on the acquisition data quality evaluation value and the preset acquisition data quality threshold. The initial electromagnetic signal data represents the set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable, and the acquisition data quality evaluation value is used to quantify the quality of the collected initial electromagnetic signal data; S2. After acquisition optimization, transmit the initial electromagnetic signal data to the cloud, and obtain the transmission data and the transmitted electromagnetic signal data. The transmission data represents the transmission information during the data transmission process, and the transmitted electromagnetic signal data represents the data after the initial electromagnetic signal data is transmitted; S3. Perform transmission evaluation based on the initial electromagnetic signal data and the transmitted electromagnetic signal data obtained after acquisition optimization to obtain the transmission data quality evaluation value, and judge whether to perform transmission optimization based on the transmission data quality evaluation value and the preset transmission data quality threshold. The transmission data quality evaluation value is used to quantify and evaluate the quality change of the electromagnetic signal data during the transmission process; S4. After transmission optimization, obtain the data real-time evaluation value based on the acquisition data quality evaluation value obtained after acquisition optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization, and judge whether to perform real-time optimization based on the data real-time evaluation value and the preset data real-time threshold. The data real-time evaluation value is used to evaluate the real-time performance of the data; The specific method for obtaining the acquisition data quality evaluation value is as follows: Process the acquisition data effective coefficient, the acquisition data consistency coefficient, and the proportion of the initial missing time period to obtain the acquisition data quality evaluation value; The specific steps for judging whether to perform acquisition optimization based on the acquisition data quality evaluation value and the preset acquisition data quality threshold are as follows: A1. Judge whether the acquisition data quality evaluation value is less than the preset acquisition data quality threshold. If the acquisition data quality evaluation value is less than the preset acquisition data quality threshold, then execute A2; otherwise, no acquisition optimization is performed; A2. Perform signal processing optimization, and at the same time judge whether the acquisition data quality evaluation value monitored after the signal processing optimization is less than the preset acquisition data quality threshold. If so, then execute A3; otherwise, end the acquisition optimization. The signal processing optimization includes removing background noise and data smoothing; A3. Adjust the sampling rate, and at the same time judge whether the acquisition data quality evaluation value obtained after the sampling rate adjustment is less than the preset acquisition data quality threshold. If so, then execute A4; otherwise, end the acquisition optimization; A4. Re-collect the initial electromagnetic signal data, and judge whether the acquisition data quality evaluation value obtained after the re-collection is less than the preset acquisition data quality threshold. If the acquisition data quality evaluation value obtained after the re-collection is less than the preset acquisition data quality threshold, then give feedback; otherwise, end the acquisition optimization; The specific method for performing transmission evaluation based on the initial electromagnetic signal data and the transmitted electromagnetic signal data obtained after acquisition optimization to obtain the transmission data quality evaluation value is as follows: Process the collected data quality evaluation value, data similarity coefficient, transmitted data integrity coefficient, and transmitted data validity coefficient to obtain the transmitted data quality evaluation value; The specific process of determining whether to perform transmission optimization based on the transmitted data quality evaluation value and the preset transmitted data quality threshold is as follows: B1. Determine whether the transmitted data quality evaluation value is less than the preset transmitted data quality threshold. If the transmitted data quality evaluation value is less than the preset transmitted data quality threshold, then execute B2; otherwise, no transmission optimization is performed. B2. Perform packet loss compensation. Determine whether the transmitted data quality evaluation value obtained after packet loss compensation is less than the preset transmitted data quality threshold. If so, then execute B3; otherwise, end the transmission optimization. B3. Send an automatic retransmission request to recover the lost data. Determine whether the transmitted data quality evaluation value obtained after retransmission is less than the preset transmitted data quality threshold. If the transmitted data quality evaluation value obtained after retransmission is less than the preset transmitted data quality threshold, then execute B4; otherwise, end the transmission optimization. B4. Perform encryption integrity verification. Determine whether the transmitted data quality evaluation value obtained after encryption integrity verification is less than the preset transmitted data quality threshold. If so, then give feedback; otherwise, end the transmission optimization. The specific method for obtaining the data real-time evaluation value based on the collected data quality evaluation value obtained after collection optimization, the transmitted data quality evaluation value obtained after transmission optimization, and the transmitted data obtained after transmission optimization is as follows: Process the transmission coefficient, the collected data quality evaluation value obtained after collection optimization, and the transmitted data quality evaluation value obtained after transmission optimization to obtain the data real-time evaluation value.

2. The on-line abnormal monitoring method for high-voltage cables according to claim 1, characterized in that: The specific method for processing the initial electromagnetic signal data obtained by the sensor is as follows; Separate the initial electromagnetic signal data to obtain the initial signal data and the initial noise data. Square the root mean square of the initial signal data to obtain the initial signal power, and square the root mean square of the initial noise data to obtain the initial noise power. Statistically analyze the initial electromagnetic signal data to obtain the initial pulse number and the initial pulse amplitude. Determine whether the initial pulse amplitude is less than the preset pulse amplitude threshold. If the initial pulse amplitude is not less than the preset pulse amplitude threshold, then record this pulse as a valid pulse and statistically obtain the total number of initial valid pulses; otherwise, do not record this pulse as a valid pulse. Obtain the initial maximum time, initial minimum time, and initial valid time period of the initial electromagnetic signal data through the time stamp of the obtained initial electromagnetic signal data. The initial maximum time represents the acquisition end time of the initial electromagnetic signal data, the initial minimum time represents the acquisition start time of the initial electromagnetic signal data, and the initial valid time period represents the time range covered by the remaining data points after removing the abnormal data points in the initial electromagnetic signal data. The abnormal data points represent the data points outside the range of the average value of the initial electromagnetic signal data plus or minus three standard deviations. Perform frequency domain analysis on the initial electromagnetic signal data through Fourier transform to obtain the initial spectral power density. The reciprocal operation is performed on the average time difference between the initial sampling points to obtain the initial actual sampling rate, and the ratio operation is performed on the initial actual sampling rate and the preset sampling rate to obtain the initial sampling rate consistency coefficient, and the initial sampling rate consistency coefficient represents the deviation between the initial actual sampling rate and the preset sampling rate; The correlation coefficient operation is performed on the obtained initial electromagnetic signal data and the standard waveform to obtain the initial waveform matching degree.

3. The online abnormal monitoring method for a high-voltage cable according to claim 2, characterized in that: The specific method for obtaining the acquisition data quality evaluation value further includes: The initial signal-to-noise ratio is obtained by analyzing the relative relationship between the obtained initial signal power and the initial noise power; The initial effective pulse ratio is obtained by analyzing the relative relationship between the total number of initial effective pulses and the initial number of pulses; The initial signal-to-noise ratio and the initial effective pulse ratio are processed to obtain the acquisition data effective coefficient, and the acquisition data effective coefficient is used to quantify the effectiveness of the acquired initial electromagnetic signal data; The initial missing time period ratio is obtained by analyzing the relative relationship between the initial maximum time, the initial minimum time, and the initial effective time period; The initial sampling rate consistency coefficient and the initial waveform matching degree are processed to obtain the acquisition data consistency coefficient, and the acquisition data consistency coefficient is used to quantify the consistency of the acquired initial electromagnetic signal data.

4. The online abnormal monitoring method for high-voltage cables according to claim 1, characterized in that: Before obtaining the transmission data quality evaluation value by performing transmission evaluation on the initial electromagnetic signal data obtained after acquisition optimization and the transmitted electromagnetic signal data, it further includes analyzing the transmitted electromagnetic signal data to obtain the transmission data parameters; The transmission data parameters include the transmitted signal power, the transmitted noise power, the total number of transmitted effective pulses, the number of transmitted pulses, and the transmitted spectral power density; The specific process for obtaining the transmission data parameters is as follows: The transmitted electromagnetic signal data is separated to obtain the transmitted signal data and the transmitted noise data, and the square operation is performed on the root mean square of the transmitted signal data to obtain the transmitted signal power; The square operation is performed on the root mean square of the transmitted noise data to obtain the transmitted noise power; The transmitted electromagnetic signal data is statistically analyzed to obtain the number of transmitted pulses and the transmitted pulse amplitude, and it is determined whether the transmitted pulse amplitude is less than the preset pulse amplitude threshold. If the transmitted pulse amplitude is not less than the preset pulse amplitude threshold, the pulse is recorded as an effective pulse, and the total number of transmitted effective pulses is statistically obtained, otherwise no operation is performed; The frequency domain analysis of the transmitted electromagnetic signal data is performed by Fourier transform to obtain the transmitted spectral power density.

5. The on-line abnormal monitoring method for a high-voltage cable according to claim 4, characterized in that: The specific method for obtaining the transmission data quality evaluation value by performing transmission evaluation on the initial electromagnetic signal data obtained after acquisition optimization and the transmitted electromagnetic signal data further includes: The correlation coefficient operation is performed on the initial electromagnetic signal data obtained after acquisition optimization and the transmitted electromagnetic signal data to obtain the data similarity coefficient; The pulse amplitude deviation is obtained by analyzing the relative relationship between the initial pulse amplitude and the transmitted pulse amplitude; The spectral deviation is obtained by analyzing the relative relationship between the initial spectral power density and the transmitted spectral power density; The pulse amplitude deviation and the spectral deviation are processed to obtain the transmission data integrity coefficient; The signal-to-noise ratio (SNR) after transmission is analyzed based on the relative relationship between the acquired signal power and noise power after transmission, and the SNR deviation is obtained by analyzing the relative relationship between the initial SNR and the SNR after transmission. The proportion of valid pulses after transmission is analyzed based on the relative relationship between the total number of valid pulses after transmission and the number of pulses after transmission, and the deviation of the proportion of valid pulses is obtained by analyzing the relative relationship between the initial proportion of valid pulses and the proportion of valid pulses after transmission. The SNR deviation and the deviation of the proportion of valid pulses are processed to obtain the effective coefficient of the transmitted data. The specific limiting expression of the quality evaluation value of the transmitted data is as follows: ； ； ； ； where i represents the serial number of a preset time point, T represents the total number of preset time periods, represents the initial electromagnetic signal data at the i-th preset time point, represents the average value of the initial electromagnetic signal data, represents the electromagnetic signal data after transmission at the i-th preset time point, represents the average value of the electromagnetic signal data after transmission, SZL represents the evaluation value of the transmission data quality, represents the evaluation value of the acquisition data quality obtained after acquisition optimization, SXS represents the data similarity coefficient, SQU represents the transmission data integrity coefficient, SYX represents the transmission data validity coefficient, CFU represents the initial pulse amplitude, SFU represents the pulse amplitude after transmission, CPI represents the initial spectral power density, SPI represents the spectral power density after transmission, XHG represents the initial signal power, ZSG represents the initial noise power, YMC represents the total number of initial effective pulses, MSH represents the initial number of pulses, SHG represents the signal power after transmission, SSG represents the noise power after transmission, SMC represents the total number of effective pulses after transmission, and SMH represents the number of pulses after transmission.

6. The online abnormal monitoring method for high-voltage cables according to claim 1, characterized in that: The specific method for obtaining the real-time evaluation value of the data based on the quality evaluation value of the acquired data after acquisition optimization, the quality evaluation value of the transmitted data after transmission optimization, and the transmitted data after transmission optimization further includes: Obtain preset transmitted data from a preset database, where the preset transmitted data includes a preset transmission rate, a preset data transmission delay, and a preset transmission distance. The transmission coefficient is analyzed based on the relative relationship between the transmitted data and the preset transmitted data. The transmission coefficient represents the deviation between the transmitted data and the preset transmitted data, and the transmitted data includes the transmission rate, the data transmission delay, and the transmission distance.

7. The on-line abnormal monitoring method for high-voltage cables according to claim 1, characterized in that: The specific process for determining whether to perform real-time optimization based on the real-time evaluation value of the data and the preset real-time evaluation threshold of the data is as follows: C1. Determine whether the real-time evaluation value of the data is less than the preset real-time evaluation threshold of the data. If the real-time evaluation value of the data is less than the preset real-time evaluation threshold of the data, then execute C2; otherwise, no real-time optimization is performed. C2. Perform traffic shaping, and determine whether the real-time evaluation value of the data obtained after traffic shaping is less than the preset real-time evaluation threshold of the data. If so, then execute C3; otherwise, end the real-time optimization. C3. Perform data compression, and determine whether the real-time evaluation value of the data obtained after data compression is less than the preset real-time evaluation threshold of the data. If so, then execute C4; otherwise, end the real-time optimization. C4. Perform path optimization, and determine whether the real-time evaluation value of the data obtained after path optimization is less than the preset real-time evaluation threshold of the data. If so, then give feedback; otherwise, end the real-time optimization.

8. A system applying the on-line abnormal monitoring method for high-voltage cables according to any one of claims 1-7, characterized in that, It includes: An initial data evaluation module, a data transmission module, a post-transmission data evaluation module, and a data real-time evaluation module; Among them, the initial data evaluation module is used to process and evaluate the initial electromagnetic signal data of the high-voltage cable obtained by the sensor to obtain the quality evaluation value of the acquired data, and determine whether to perform acquisition optimization based on the quality evaluation value of the acquired data and the preset quality threshold of the acquired data. The initial electromagnetic signal data represents the set of electromagnetic signals collected for monitoring the abnormal conditions of the high-voltage cable, and the quality evaluation value of the acquired data is used to quantify the quality of the collected initial electromagnetic signal data. The data transmission module is used to transmit the initial electromagnetic signal data to the cloud after acquisition optimization, and obtain the transmitted data and the electromagnetic signal data after transmission. The transmitted data represents the transmission information during the data transmission process, and the electromagnetic signal data after transmission represents the data after the initial electromagnetic signal data is transmitted. The post - transmission data evaluation module is used to perform transmission evaluation based on the initial electromagnetic signal data obtained after acquisition optimization and the post - transmission electromagnetic signal data to obtain a transmission data quality evaluation value, and determine whether to perform transmission optimization based on the transmission data quality evaluation value and a preset transmission data quality threshold. The transmission data quality evaluation value is used to quantitatively evaluate the quality change of the electromagnetic signal data during the transmission process; The data real - time evaluation module is used to obtain a data real - time evaluation value based on the acquisition data quality evaluation value obtained after acquisition optimization, the transmission data quality evaluation value obtained after transmission optimization, and the transmission data obtained after transmission optimization after transmission optimization, and determine whether to perform real - time optimization based on the data real - time evaluation value and a preset data real - time evaluation threshold. The data real - time evaluation value is used to evaluate the real - time nature of the data.

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