An intelligent analysis system for power cable withstand voltage test data

Abstract

The present invention discloses an intelligent analysis system for power cable withstand voltage test data, comprising an input unit; a data acquisition module; a data preprocessing module; a feature extraction module; an intelligent analysis module; a data storage module for storing collected original data, preprocessed data and analysis results of the intelligent analysis module; and a user interaction module. In view of the problem that the thermal conductivity of cable materials is ignored in traditional withstand voltage test data analysis, the thermal conductivity is incorporated into the evaluation model to accurately reflect the heat dissipation differences of cables made of different materials in the withstand voltage test, thereby significantly improving the accuracy of insulation status evaluation, avoiding unnecessary repairs or replacements due to misjudgment, and directly reducing operation and maintenance costs. At the same time, analysis based on thermal conductivity can more keenly capture the aging trend of insulation performance, effectively improve the accuracy of withstand voltage test results, give early warning of potential faults, and enhance the operational reliability of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of cable detection, and in particular to an intelligent analysis system for power cable withstand voltage test data. Background Art

[0002] As a key component of modern power transmission systems, the insulation performance of power cables is directly related to the safe and stable operation of power systems. To ensure the long-term reliability of power cables, withstand voltage testing is widely used as an important testing method. This test simulates the cable's operating conditions under extreme conditions by applying a test voltage higher than the normal operating voltage to the power cable, thereby evaluating its insulation performance. However, traditional withstand voltage test data analysis often has limitations, particularly when considering the impact of cable material properties on test results.

[0003] Traditional methods for analyzing withstand voltage test data primarily focus on simple statistics and analysis of electrical parameters such as voltage, current, and partial discharge collected during the test. While these methods can provide a certain degree of insight into the insulation condition of power cables, they overlook a critical factor: the thermal conductivity of the cable material. Thermal conductivity, the ability of a material to conduct heat, plays a crucial role in withstand voltage testing of power cables. Under high voltage, heat is generated within the power cable, and the thermal conductivity of the cable material directly affects its heat dissipation performance. If the thermal conductivity of the cable material is low, heat cannot be dissipated quickly, resulting in localized temperature increases within the cable. This localized overheating accelerates the aging of the insulation material, degrading its insulation performance, and thus affecting the accuracy of the withstand voltage test results and the prediction of the remaining service life of the power cable.

[0004] In the patent document with publication number CN119378288A, thermal conductivity is not taken into consideration. This makes it impossible to fully and accurately reflect the actual situation when evaluating the insulation status of power cables, which can easily lead to misjudgment and bring potential risks to the safe operation of the power system. For example, when conducting a withstand voltage test on power cables made of different materials, if the difference in thermal conductivity is not taken into account, similar electrical parameter performance may be obtained, but in fact their insulation performance and remaining service life may be very different. This inaccurate assessment not only increases the risk of power cable failure, but also leads to unnecessary repairs or replacements, increasing the operation and maintenance costs of the power system. Summary of the Invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of this application to avoid obscuring the purpose of this section, the abstract and the title of the invention, and such simplifications or omissions should not be used to limit the scope of the present invention.

[0006] In view of the above-mentioned problems existing in the existing intelligent analysis system for power cable withstand voltage test data, the present invention is proposed.

[0007] Therefore, the object of the present invention is to provide an intelligent analysis system for power cable withstand voltage test data.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions: a power cable withstand voltage test data intelligent analysis system, comprising: an input unit for receiving test parameters input by a user;

[0009] Data acquisition module, used to collect data in real time during the power cable withstand voltage test;

[0010] A data preprocessing module is used to preprocess the collected data and obtain the preprocessed data;

[0011] Feature extraction module, used to extract feature parameters from preprocessed data;

[0012] Intelligent analysis module, which evaluates the insulation status of power cables based on extracted characteristic parameters and predicts the remaining service life of power cables;

[0013] The data storage module is used to store the collected raw data, pre-processed data and the analysis results of the intelligent analysis module;

[0014] The user interaction module is used to display the insulation status assessment results and remaining service life of the power cable to the user and provide early warning function.

[0015] As a preferred solution of the intelligent analysis system for power cable withstand voltage test data of the present invention, the intelligent analysis module includes a classifier based on machine learning, which is used to classify the insulation status of the power cable and determine its insulation status, wherein the insulation status includes a normal state, an aging state, or a fault state;

[0016] An evaluation model is used to calculate the remaining useful life of power cables based on the classification results.

[0017] As a preferred solution of the intelligent analysis system for power cable withstand voltage test data of the present invention, the calculation formula of the evaluation model is:

[0018]

[0019] Among them, V rated is the rated voltage of the power cable, V pd is the partial discharge inception voltage, f rep For discharge repetition, is the pulse width, and k is the thermal conductivity constant determined according to the thermal conductivity of the cable material.

[0020] As a preferred solution of the power cable withstand voltage test data intelligent analysis system of the present invention, the formula for determining the value of the thermal conductivity constant k is:

[0021]

[0022] in, is the thermal conductivity of the cable material, and α is the calibration coefficient, which is used to adjust the value range of the thermal conductivity constant k to make the value reasonable. Here, α is set to 0.1.

[0023] As a preferred solution of the intelligent analysis system for power cable withstand voltage test data of the present invention, the data acquisition module further includes an environmental parameter acquisition unit for collecting temperature, humidity and air pressure data of the test environment.

[0024] As a preferred solution of the power cable withstand voltage test data intelligent analysis system of the present invention, the user interaction module further includes a warning threshold setting unit, and the user can set different warning thresholds according to the actual operation of the power cable.

[0025] As a preferred solution of the power cable withstand voltage test data intelligent analysis system of the present invention, the intelligent analysis module also includes a trend analysis unit for analyzing the changing trend of the power cable insulation status and predicting the insulation status in the future.

[0026] As a preferred solution of the power cable withstand voltage test data intelligent analysis system of the present invention, wherein: the data storage module adopts a distributed storage architecture, which can store a large amount of test data and analysis results, and supports rapid retrieval and backup of data;

[0027] The data storage module also includes a data analysis and optimization unit for analyzing and optimizing the stored data.

[0028] As a preferred solution of the power cable withstand voltage test data intelligent analysis system of the present invention, wherein: the data preprocessing module includes:

[0029] The filtering unit uses a Butterworth low-pass filter to filter the collected data;

[0030] Denoising unit, which uses wavelet transform to perform denoising on the filtered data;

[0031] Normalization unit, which uses the minimum-maximum normalization method to normalize the denoised data;

[0032] The filtering formula of the filtering unit is:

[0033]

[0034] Among them, y(t) is the function value of the filtered output signal at time t, which is the signal after filtering, that is, the final desired result; x(t) is the function value of the original input signal at time t, which is the original data obtained from the data acquisition module and needs to be filtered to remove noise; b i is the forward coefficient of the filter, a j is the backward coefficient of the filter, n is the order of the filter, i is the time delay index of the input signal, and j is the time delay index of the output signal.

[0035] Beneficial effects of the present invention: The present invention addresses the problem of ignoring the thermal conductivity of cable materials in traditional voltage withstand test data analysis. By incorporating thermal conductivity into the evaluation model, the heat dissipation differences of cables made of different materials in the voltage withstand test can be accurately reflected, thereby significantly improving the accuracy of insulation status assessment, avoiding unnecessary repairs or replacements due to misjudgment, and directly reducing operation and maintenance costs. At the same time, analysis based on thermal conductivity can more keenly capture the aging trend of insulation performance, effectively improve the accuracy of voltage withstand test results, provide early warning of potential faults, and enhance the operational reliability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0037] Figure 1 Schematic diagram of the overall architecture of the power cable withstand voltage test data intelligent analysis system of the present invention.

[0038] Figure 2 This is a diagram of the computer equipment of the power cable withstand voltage test data intelligent analysis system of the present invention. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0040] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0041] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0042] Furthermore, the present invention is described in detail with reference to schematic diagrams. For ease of illustration, when describing the embodiments of the present invention, cross-sectional views illustrating device structures may be partially enlarged and not to scale. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of protection of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0043] Example, see Figure 1-2 As shown in the figure, an intelligent analysis system for power cable withstand voltage test data includes an input unit for receiving test parameters input by a user; a data acquisition module for real-time acquisition of data during the power cable withstand voltage test; a data preprocessing module for preprocessing the collected data and obtaining preprocessed data; a feature extraction module for extracting feature parameters from the preprocessed data; an intelligent analysis module for evaluating the insulation state of the power cable based on the extracted feature parameters and predicting the remaining service life of the power cable; a data storage module for storing the collected original data, preprocessed data and the analysis results of the intelligent analysis module; a user interaction module for displaying the insulation state evaluation results and the remaining service life of the power cable to the user and providing an early warning function;

[0044] The user interaction module of the present invention has a warning threshold setting function. Combined with the real-time evaluation capability of the intelligent analysis module, it can promptly detect abnormal changes in the insulation state of the power cable and issue a warning signal. Compared with traditional methods, the present invention can more keenly capture early signs that may lead to failures because it takes into account the impact of thermal conductivity on insulation performance. This timely and effective fault warning function provides power system operation and maintenance personnel with sufficient time to take preventive measures, avoid the occurrence of failures, and reduce the economic losses and social impacts caused by failures.

[0045] Specifically, the intelligent analysis module includes a classifier based on machine learning, which is used to classify the insulation status of the power cable and determine its insulation status, which includes normal state, aging state or fault state;

[0046] An evaluation model is used to calculate the remaining service life of power cables based on the classification results. Based on the model's consideration of thermal conductivity, the evaluation model of the present invention can more scientifically predict the remaining service life of power cables, avoiding the problem of inaccurate remaining service life predictions often caused by traditional methods that ignore the impact of thermal conductivity on insulation aging. By introducing thermal conductivity-related parameters and combining them with other electrical parameters, a more comprehensive and accurate prediction model is constructed. This model can more realistically reflect the performance change trends of cables during long-term operation, providing power system operation and maintenance personnel with a more reliable decision-making basis, helping them to reasonably arrange cable maintenance and replacement plans, avoid power outages caused by cable failures, and improve the power supply reliability and economy of the power system.

[0047] Furthermore, the calculation formula of the evaluation model is:

[0048]

[0049] Among them, V rated is the rated voltage of the power cable, V pd is the partial discharge inception voltage, f rep is the discharge repetition rate, is the pulse width, and k is the thermal conductivity constant determined according to the thermal conductivity of the cable material.

[0050] Thermal conductivity is the ability of a material to conduct heat. In the withstand voltage test of power cables, thermal conductivity affects the heat dissipation performance of the cable under high voltage. If the thermal conductivity of the cable material is low, heat is not easily dissipated, which may cause local overheating, thereby affecting the insulation performance and withstand voltage of the cable. By comprehensively considering the thermal conductivity of the cable material, the limitations of traditional methods that rely solely on electrical parameters for analysis are overcome. Thermal conductivity, as a key factor affecting the heat dissipation performance of the cable, is directly related to the aging rate of the insulation material under high voltage and the stability of the insulation performance. Incorporating thermal conductivity into the analysis model can more accurately reflect the insulation state of the power cable under actual operating conditions, thereby significantly improving the accuracy of the insulation state assessment. This enables power system operation and maintenance personnel to more reliably determine whether the cable is in a normal state, an aged state, or a faulty state, providing stronger guarantees for the safe operation of the power system.

[0051] Therefore, thermal conductivity is an important factor affecting the cable withstand voltage test data. The heat dissipation characteristics of different materials can be reflected by adjusting the constant k.

[0052] Among them, the formula for the thermal conductivity constant k is:

[0053]

[0054] in, is the thermal conductivity of the cable material, α is the calibration coefficient, which is used to adjust the value range of the thermal conductivity constant k to make the value reasonable. Here, α is set to 0.1.

[0055] For example, if the cable uses polyethylene insulation material, its thermal conductivity is about 0.4W / m·k, so the value of k can be calculated as ,

[0056] If the cable uses rubber insulation material, its thermal conductivity is about 0.15W / m·k, so the value of k can be calculated as In this way, the thermal conductivity constant k can be calculated based on the thermal conductivity of the cable material. Adjustments are made to more accurately reflect the impact of different materials' heat dissipation characteristics on the withstand voltage test in the evaluation model.

[0057] It should be noted that the data acquisition module also includes an environmental parameter acquisition unit for collecting temperature, humidity and air pressure data of the test environment. The user interaction module also includes an early warning threshold setting unit. The user can set different early warning thresholds according to the actual operation of the power cable. The temperature, humidity and air pressure data of the test environment are collected through the data acquisition module and incorporated into the analysis model, so that the system can adapt to voltage tests under different environmental conditions. At the same time, when the system analyzes power cables made of different materials, it can conduct targeted evaluations based on their thermal conductivity differences, avoiding the evaluation bias caused by ignoring material differences in traditional methods. This adaptability to a variety of cable materials and operating environments gives the present invention a wider range of applications, can meet the detection needs of different types of cables in the power system, and provides strong support for the comprehensive maintenance of the power system.

[0058] In particular, the intelligent analysis module also includes a trend analysis unit for analyzing the changing trend of the power cable insulation status and predicting the insulation status in the future. The data storage module adopts a distributed storage architecture, which can store a large amount of test data and analysis results, and supports rapid data retrieval and backup.

[0059] The data storage module also includes a data analysis and optimization unit for analyzing and optimizing the stored data.

[0060] Furthermore, the data preprocessing module includes,

[0061] The filtering unit uses a Butterworth low-pass filter to filter the collected data;

[0062] Denoising unit, which uses wavelet transform to perform denoising on the filtered data;

[0063] Normalization unit, which uses the minimum-maximum normalization method to normalize the denoised data;

[0064] The filtering formula of the filtering unit is:

[0065]

[0066] Among them, y(t) is the function value of the filtered output signal at time t, which is the signal after filtering, that is, the final desired result; x(t) is the function value of the original input signal at time t, which is the original data obtained from the data acquisition module and needs to be filtered to remove noise; b i is the forward coefficient of the filter, a j is the backward coefficient of the filter, n is the order of the filter, i is the time delay index of the input signal, and j is the time delay index of the output signal; a Butterworth low-pass filter is used here, b i , a j It can be calculated using the design formula of the Butterworth filter;

[0067] The purpose of filtering is to remove high-frequency noise and retain the main features of the signal. A low-pass filter is used to filter the collected voltage, current, partial discharge and temperature data. Its transfer function is:

[0068]

[0069] Where f is the signal frequency, f c is the cutoff frequency, n is the order of the filter;

[0070] Then, denoising is performed. The purpose of denoising is to further reduce the impact of noise on the signal. Wavelet transform is used to perform denoising. The formula is:

[0071]

[0072] Where x(n) represents the input signal, is the wavelet basis function, C j,k are the wavelet coefficients;

[0073] The noise in the wavelet coefficients is removed by soft threshold processing, and the expression formula is:

[0074]

[0075] in, Represents the threshold parameter, and its selection method formula is:

[0076]

[0077] Where σ is the standard deviation of the noise, which can be estimated from the high-frequency part of the signal, N is the length of the signal, and ln is the natural logarithm;

[0078] Here, for example, assuming that the signal length N = 1024 and the noise standard deviation σ = 0.1, the threshold parameter for,

[0079]

[0080] The function sign(x) is a sign function that returns the sign of the input value and is expressed as follows:

[0081]

[0082] Then, normalization is required, using the minimum-maximum normalization method. For the input data x, the normalized data for,

[0083]

[0084] Among them, min(x) is the minimum value of the data, max(x) is the maximum value of the data, and normalization processing scales the data to the range of [0,1] to enhance the efficiency and accuracy of subsequent analysis.

[0085] Furthermore, if the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or the portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. Conventional storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0086] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0087] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0088] Operation Process: The operator first activates the power cable withstand voltage test data intelligent analysis system, which then enters a self-test state, comprehensively checking the operational status of the hardware modules and software systems to ensure that everything is functioning properly. After the self-test is complete, the system automatically loads default test parameters, which cover key information such as the rated voltage of the power cable and the initial temperature, humidity, and air pressure of the test environment. The operator can flexibly adjust these parameters through the input unit according to actual test requirements to ensure test accuracy and reliability.

[0089] After the test parameters are set, the operator enters the specific parameters for the withstand voltage test through the input unit. These parameters include the starting voltage, ending voltage, test time, and partial discharge threshold. These parameters provide clear guidance for subsequent data collection and analysis. At the same time, the operator must carefully set the warning threshold for insulation condition assessment based on the actual operation of the power cable using the warning threshold setting unit in the user interaction module. Setting this threshold is crucial. When the assessment result falls below this threshold, the system will promptly issue a warning signal, prompting the operator to take appropriate measures to ensure the safe operation of the power cable.

[0090] With the official start of the test, the data acquisition module quickly went into operation, collecting various data in real time during the power cable withstand voltage test. This data includes key indicators such as voltage, current, partial discharge, and temperature, which directly reflect the performance of the power cable during the withstand voltage test. Simultaneously, the environmental parameter acquisition unit also simultaneously collects temperature, humidity, and air pressure data from the test environment. These environmental parameters are also essential for a comprehensive assessment of the power cable's insulation condition. The collected data is quickly and accurately transmitted to the data preprocessing module via data lines or wireless transmission, preparing for further data processing.

[0091] After receiving the collected data, the data preprocessing module immediately activates the filtering unit to filter the data, effectively removing high-frequency noise and preserving the signal's key features, providing a clearer and more accurate data foundation for subsequent analysis. Next, the denoising unit takes over, using advanced wavelet transform technology to denoise the filtered data, further reducing the impact of noise on the signal and making the data purer. Finally, the normalization unit takes over, using the minimum-maximum normalization method to normalize the denoised data and scale it to a uniform range. This process not only enhances the efficiency of subsequent analysis but also improves the accuracy of the analysis results, providing a strong guarantee for the efficient operation of the feature extraction and intelligent analysis modules.

[0092] After data preprocessing is complete, the feature extraction module quickly takes over, accurately extracting characteristic parameters closely related to the power cable's insulation condition from the preprocessed data. These characteristic parameters act as a "fingerprint" of the power cable's insulation condition, providing critical information for subsequent intelligent analysis. Simultaneously, the machine learning-based classifier within the intelligent analysis module is also fully operational, meticulously classifying the insulation condition of the power cable, accurately determining whether it is normal, aged, or faulty. Once the classification is complete, the evaluation model uses the classification results to scientifically calculate the remaining service life of the power cable, providing valuable reference information for its safe operation and maintenance.

[0093] At the same time, the data storage module captures and properly stores all collected raw data, preprocessed data, and analysis results from the intelligent analysis module. This data not only provides a complete record of the current test but also lays a solid foundation for subsequent query and analysis. The user interaction module acts as a "window" to the system, clearly displaying the insulation condition assessment results and remaining service life of the power cable to the user, allowing them to intuitively understand the operating status of the power cable. When the assessment result falls below the set warning threshold, the system automatically issues a warning signal, prompting the operator to take timely measures to ensure the safe operation of the power cable.

[0094] After the test is successfully completed, the operator presses the shutdown button, and the system begins its shutdown process. Before shutting down, the system automatically saves existing data and analysis results to ensure test integrity and traceability. Finally, the system performs a comprehensive self-check to confirm that all modules have been safely shut down, then officially enters a dormant state, awaiting the next test. The entire operation process is seamlessly linked and integrated, fully demonstrating the efficiency, accuracy, and reliability of the intelligent analysis system for power cable withstand voltage test data, providing strong technical support for the safe operation and maintenance of power cables.

[0095] It is important to note that the configuration and arrangement of the present application, as illustrated in various exemplary embodiments, are illustrative only. Although only a few embodiments are described in detail in this disclosure, those reading this disclosure will readily appreciate that numerous modifications are possible (e.g., variations in the size, dimensions, structure, shape, and proportions of various components, as well as parameter values ​​(e.g., temperature, pressure, etc.), mounting arrangements, use of materials, color, orientation, etc.) without materially departing from the novel teachings and advantages of the subject matter described herein. For example, components shown as integrally formed may be comprised of multiple parts or components, the positions of components may be inverted or otherwise altered, and the nature, number, or position of discrete components may be modified or changed. Therefore, all such modifications are intended to be encompassed within the scope of this invention. The order or sequence of any process or method steps may be altered or reordered according to alternative embodiments. Other substitutions, modifications, changes, and omissions may be made in the design, operating conditions, and arrangement of the exemplary embodiments without departing from the scope of this invention. Therefore, this invention is not limited to a particular embodiment but extends to a variety of modifications that still fall within the scope of the appended claims.

[0096] Additionally, in order to provide a concise description of exemplary embodiments, all features of an actual embodiment may not be described (ie, those features that are not relevant to the best mode presently contemplated for carrying out the invention or those that are not relevant to implementing the invention).

[0097] It will be appreciated that in the development of any actual embodiment, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but will, for those of ordinary skill having the benefit of this disclosure, be a routine undertaking of design, fabrication, and production without undue experimentation.

[0098] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent analysis system for power cable withstand voltage test data, characterized by: include, An input unit, used for receiving test parameters input by a user; Data acquisition module, used to collect data in real time during the power cable withstand voltage test; A data preprocessing module is used to preprocess the collected data and obtain the preprocessed data; Feature extraction module, used to extract feature parameters from preprocessed data; Intelligent analysis module, which evaluates the insulation status of power cables based on extracted characteristic parameters and predicts the remaining service life of power cables; The data storage module is used to store the collected raw data, pre-processed data and the analysis results of the intelligent analysis module; User interaction module, used to show users the insulation status assessment results and remaining service life of power cables, and provide early warning functions; The intelligent analysis module includes a classifier based on machine learning, which is used to classify the insulation status of the power cable and determine its insulation status, wherein the insulation status includes a normal state, an aging state or a fault state; An evaluation model for calculating the remaining useful life of the power cable based on the classification results; The calculation formula of the evaluation model is: Among them, V rated is the rated voltage of the power cable, V pd is the partial discharge inception voltage, f rep is the discharge repetition rate, τ is the pulse width, k is the thermal conductivity constant determined by the thermal conductivity of the cable material, and RUL is the remaining service life; The formula for the thermal conductivity constant k is: Where λ is the thermal conductivity of the cable material, and α is the calibration coefficient used to adjust the value range of the thermal conductivity constant k so that the value is reasonable. Here, α is set to 0.

1.

2. The intelligent analysis system for power cable withstand voltage test data according to claim 1, characterized in that: The data acquisition module also includes an environmental parameter acquisition unit for collecting temperature, humidity and air pressure data of the test environment.

3. The intelligent analysis system for power cable withstand voltage test data according to claim 1 or 2, characterized in that: The user interaction module also includes a warning threshold setting unit, and the user can set different warning thresholds according to the actual operation of the power cable.

4. The intelligent analysis system for power cable withstand voltage test data according to claim 3, characterized in that: The intelligent analysis module also includes a trend analysis unit for analyzing the changing trend of the insulation state of the power cable and predicting the insulation state within a period of time in the future.

5. The intelligent analysis system for power cable withstand voltage test data according to claim 4, characterized in that: The data storage module adopts a distributed storage architecture, which can store a large amount of test data and analysis results, and supports rapid retrieval and backup of data; The data storage module also includes a data analysis and optimization unit for analyzing and optimizing the stored data.

6. The intelligent analysis system for power cable withstand voltage test data according to claim 1, characterized in that: The data preprocessing module includes: The filtering unit uses a Butterworth low-pass filter to filter the collected data; Denoising unit, which uses wavelet transform to perform denoising on the filtered data; Normalization unit, which uses the minimum-maximum normalization method to normalize the denoised data; The filtering formula of the filtering unit is: Among them, y(t) is the function value of the filtered output signal at time t, which is the signal after filtering, that is, the final desired result; x(t) is the function value of the original input signal at time t, which is the original data obtained from the data acquisition module and needs to be filtered to remove noise; b i is the forward coefficient of the filter, a j is the backward coefficient of the filter, n is the order of the filter, i is the time delay index of the input signal, and j is the time delay index of the output signal.

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