Power cable diagnosis method, equipment, medium and product

Abstract

The invention relates to the technical field of cable state monitoring, in particular to a power cable diagnosis method and device, a medium and a product, and the method comprises the steps: obtaining a preliminary diagnosis parameter and a diagnosis confirmation parameter collected by a sensor array, carrying out the preliminary diagnosis of a cable based on the preliminary diagnosis parameter, and when the preliminary diagnosis result of the cable is that there is an abnormality, carrying out the diagnosis of the power cable. The cable secondary diagnosis is carried out based on the diagnosis confirmation parameters, the cable definite diagnosis result is determined, comprehensive evaluation of the cable state can be realized through combination of the preliminary diagnosis parameters and the diagnosis confirmation parameters, and the accuracy of power cable diagnosis is improved. And furthermore, when the cable is confirmed to be abnormal, an insulation resistance test is executed to collect an insulation resistance value, fault detection operation selection is performed based on the insulation resistance value, target fault detection operation is determined, and fault detection operation is executed on the cable according to the target fault detection operation. And finally, performing cable fault analysis based on the fault detection data, and determining a fault point position and a fault type.

Description

Technical Field

[0001] The present application relates to the technical field of cable status monitoring, and in particular to a power cable diagnosis method, equipment, medium and product. Background Art

[0002] With the rapid development of smart grid and energy Internet, power cables are an indispensable part of power systems, and their operation safety and reliability are increasingly valued. Traditional power cable diagnosis methods mostly rely on offline detection, such as using a megohmmeter to measure insulation resistance and conduction tests. Although these methods can determine whether there is a fault in the cable to a certain extent, they cannot quickly and accurately locate the fault point, and the operation is cumbersome and inefficient.

[0003] In recent years, with the rapid development of electronic technology, signal processing technology and artificial intelligence technology, online detection technology for power cables has gradually become possible. This online detection technology avoids the downtime operation in offline detection to a certain extent. However, the current online detection method usually only uses any one of the modes of partial discharge detection, temperature measurement and dielectric loss test to detect the health status of power cables. This method is often limited to a specific indicator and is difficult to fully reflect the true health status of the cable, resulting in low accuracy in power cable fault diagnosis.

[0004] Therefore, how to improve the accuracy of power cable diagnosis is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0005] The purpose of this application is to provide a power cable diagnosis method, device, medium and product to solve at least one of the above technical problems.

[0006] The above invention objectives of the present application are achieved through the following technical solutions: In a first aspect, the present application provides a power cable diagnosis method, which adopts the following technical solution: A power cable diagnosis method, comprising: Acquire preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array, wherein the preliminary diagnostic parameters include: cable temperature data and DC component; the diagnostic confirmation parameters include: partial discharge signal, cable current data and cable voltage data; Performing a preliminary diagnosis of the cable based on the preliminary diagnosis parameters, and when the preliminary diagnosis result of the cable is abnormal, performing a secondary diagnosis of the cable based on the diagnosis confirmation parameters to determine a confirmed result of the cable; When the cable is diagnosed as abnormal, an insulation resistance test is performed to collect an insulation resistance value, a fault detection operation is selected based on the insulation resistance value, a target fault detection operation is determined, and a fault detection operation is performed on the cable according to the target fault detection operation; Fault detection data is acquired, and cable fault analysis is performed based on the fault detection data to determine the location of the fault point and the type of fault.

[0007] By adopting the above technical solution, the preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array are obtained. The sensor array can cover a wider monitoring range, capture more subtle changes in the cable status, and provide richer data support for cable fault diagnosis. The cable is preliminarily diagnosed based on the preliminary diagnostic parameters. When the preliminary diagnosis result of the cable is abnormal, the cable is secondary diagnosed based on the diagnostic confirmation parameters to determine the cable diagnosis result. By combining the preliminary diagnostic parameters and the diagnostic confirmation parameters, a comprehensive assessment of the cable status can be achieved, which improves the accuracy of power cable diagnosis. Furthermore, when the cable diagnosis result is abnormal, an insulation resistance test is performed to collect the insulation resistance value, and a fault detection operation is selected based on the insulation resistance value, the target fault detection operation is determined, and the fault detection operation is performed on the cable according to the target fault detection operation. Finally, the fault detection data is obtained, and the cable fault analysis is performed based on the fault detection data to determine the fault point location and fault type.

[0008] In a preferred example, the present application may be further configured as follows: performing secondary cable diagnosis based on the diagnosis confirmation parameter to determine the cable diagnosis result includes: Extracting features based on the partial discharge signal to determine partial discharge features, and performing abnormal discharge detection based on the partial discharge features to determine abnormal discharge detection results, wherein the abnormal discharge detection results include: whether abnormal discharge exists and the severity level of abnormal discharge; Performing dielectric loss calculation based on the cable current data and the cable voltage data to determine a dielectric loss factor and a loss tangent; Obtaining a standard dielectric loss factor and a standard loss tangent, performing dielectric loss test diagnosis based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent, and determining a cable insulation performance diagnosis result, wherein the cable insulation performance diagnosis result includes: good insulation performance and abnormal insulation performance; The abnormal discharge detection result and the cable insulation performance diagnosis result are combined to determine the cable diagnosis result.

[0009] In a preferred example, the present application may be further configured as follows: the selection of a fault detection operation based on the insulation resistance value to determine a target fault detection operation includes: Acquire the cable characteristic impedance, compare the resistance values ​​based on the insulation resistance value and the cable characteristic impedance, and when the insulation resistance value is greater than the cable characteristic impedance, determine that the target fault detection operation is an impulse high-voltage flashover method or a traveling wave method fault location; When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be a low voltage pulse method or a DC high voltage pulse method.

[0010] In a preferred example, the present application may be further configured as follows: after performing cable fault analysis based on the fault detection data and determining the location of the fault point and the fault type, the present application may further include: The fault point location and the fault type are stored in a cable fault database, wherein the cable fault data of different areas are stored in different partitions in the cable fault database according to the fault point location; When a cable quality assessment instruction carrying a cable laying area is detected, based on the cable laying area in the cable quality assessment instruction, cable fault data is screened in the cable fault database to determine target cable fault data; A cable health assessment is performed based on the target cable fault data to generate a cable health assessment report.

[0011] In a preferred example, the present application may be further configured as follows: after obtaining the preliminary diagnostic parameters collected by the sensor array, the following further includes: Perform cable heating diagnosis based on the cable temperature data in the preliminary diagnostic parameters, and determine the cable heating diagnosis result; When the cable heating diagnosis result is that the cable is overheated, overheat decomposition gas data collected by the gas sensor is obtained, and an overheat level analysis is performed based on the overheat decomposition gas data to determine the cable overheat level.

[0012] In a preferred example, the present application may be further configured as follows: after performing cable fault analysis based on the fault detection data and determining the location of the fault point and the fault type, the present application may further include: Acquire power cable network information, and construct a model based on the power cable network information to obtain a three-dimensional model of the cable network; A fault visualization display is performed based on the fault point location, the fault type and the cable network three-dimensional model to obtain a fault source labeled cable model, wherein the fault source labeled cable model is used to intuitively display the distribution location of the fault source in the power cable network.

[0013] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein the at least one application is stored in the memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned power cable diagnosis method.

[0014] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute the above-mentioned power cable diagnosis method.

[0015] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product comprises a computer program, wherein when the computer program is executed by a processor, the power cable diagnosis method is implemented.

[0016] In summary, the present application includes at least one of the following beneficial technical effects: The sensor array can cover a wider monitoring range, capture more subtle changes in cable status, and provide richer data support for cable fault diagnosis by acquiring the preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array. The cable is preliminarily diagnosed based on the preliminary diagnostic parameters. When the preliminary diagnostic result of the cable is abnormal, the cable is secondary diagnosed based on the diagnostic confirmation parameters to determine the cable diagnosis result. By combining the preliminary diagnostic parameters and diagnostic confirmation parameters, a comprehensive assessment of the cable status can be achieved, thereby improving the accuracy of power cable diagnosis. Furthermore, when the cable diagnosis result is abnormal, an insulation resistance test is performed to collect the insulation resistance value, and a fault detection operation is selected based on the insulation resistance value, the target fault detection operation is determined, and the fault detection operation is performed on the cable according to the target fault detection operation. Finally, the fault detection data is acquired, and the cable fault analysis is performed based on the fault detection data to determine the location of the fault point and the type of fault.

[0017] Since different fault detection methods are suitable for different fault types and resistance ranges, selecting a suitable fault detection method can significantly improve the accuracy and efficiency of fault detection and reduce the possibility of misjudgment and missed judgment. Therefore, the cable characteristic impedance is obtained, and the resistance value is compared based on the insulation resistance value and the cable characteristic impedance. When the insulation resistance value is greater than the cable characteristic impedance, the target fault detection operation is determined to be the impulse high-voltage flashover method or the traveling wave method fault location. When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be the low-voltage pulse method or the DC high-voltage pulse method. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of a power cable diagnosis method according to one embodiment of the present application; Figure 2 It is a structural schematic diagram of a power cable diagnostic system according to one embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device according to one embodiment of the present application. DETAILED DESCRIPTION

[0019] The following combination Figures 1 to 3 This application is described in further detail.

[0020] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0021] In order to make the purpose, technical scheme and advantages of the embodiment of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application. It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the data related to the object is involved in the embodiment of the present application, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in accordance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiment, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained, and the embodiment also needs to be implemented with the authorization and consent of the object.

[0022] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0023] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0024] The embodiment of the present application provides a power cable diagnosis method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102, step S103 and step S104, wherein: Step S101: obtaining preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array, wherein the preliminary diagnostic parameters include: cable temperature data and DC components; the diagnostic confirmation parameters include: partial discharge signals, cable voltage data and cable current data.

[0025] For the embodiments of the present application, in order to improve the accuracy of power cable diagnosis, a high-precision and high-sensitivity sensor array is used to monitor cable parameters such as temperature, current, voltage, DC component, discharge signal, cable current data and cable voltage data in real time. Compared with traditional sensors, the sensor array can cover a wider monitoring range, capture more subtle changes in cable status, and provide richer data support for cable fault diagnosis.

[0026] Specifically, the preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array are obtained, wherein the preliminary diagnostic parameters include: cable temperature data and DC component; the diagnostic confirmation parameters include: partial discharge signal, cable current data and cable voltage data. For the cable temperature data in the preliminary diagnostic parameters, the temperature of the cable surface or the temperature distribution inside the cable is measured in real time by the temperature sensor. The cable temperature data can reflect the operating status of the cable. Too high or too low temperature may indicate that there is a problem with the cable. If an unbalanced current or leakage current is generated in the cable, the current sensor can collect the cable DC component, and the size of the DC component can reflect the insulation condition of the cable. At the same time, partial discharge is one of the important precursors of cable insulation damage. Therefore, a high-frequency partial discharge sensor is used to detect whether there is a partial discharge signal in the cable, and the insulation state and health of the cable are judged by detecting the amplitude, phase and frequency of the discharge signal. The cable current data and the cable voltage data are the data obtained by performing a dielectric loss test on the cable, so as to facilitate the subsequent calculation of the dielectric loss factor and loss tangent of the cable. The dielectric loss factor and loss tangent are used to reflect the aging of the cable insulation and are an important reference for evaluating the insulation performance of the cable.

[0027] Step S102: Perform preliminary diagnosis of the cable based on preliminary diagnosis parameters. When the preliminary diagnosis result of the cable is abnormal, perform secondary diagnosis of the cable based on diagnosis confirmation parameters to determine the diagnosis result of the cable.

[0028] For the embodiments of the present application, the cable is a key component of power transmission, and its quality and safety are of vital importance. The cable temperature data and DC component are used as preliminary diagnostic parameters to provide preliminary information for diagnosing the operating status of the cable, so as to quickly and easily preliminarily determine whether the cable is overloaded, has poor heat dissipation, or has insulation damage or aging. Furthermore, when the preliminary diagnostic results show that the cable is abnormal, the diagnostic confirmation parameters are used to perform a more detailed and in-depth fault diagnosis on the cable, so as to reveal more complex faults or defects that may exist inside the cable. By combining the preliminary diagnostic parameters and the diagnostic confirmation parameters, a comprehensive assessment of the cable status can be achieved, thereby improving the accuracy of power cable diagnosis.

[0029] Specifically, a temperature alarm threshold is obtained, and a temperature comparison is performed based on the cable temperature data in the preliminary diagnostic parameters and the temperature alarm threshold. If the cable temperature data is higher than the temperature alarm threshold, it indicates that the cable is overheated, and the preliminary diagnosis result is determined to be abnormal, wherein the temperature alarm threshold is a reasonable alarm threshold set by comprehensively considering the material, specification, operating environment and safety standards of the cable, and the specific value of the temperature alarm threshold is no longer limited in the embodiment of the present application. At the same time, a DC component alarm threshold is obtained, and a DC component comparison is performed based on the DC component in the preliminary diagnostic parameters and the DC component alarm threshold. If the DC component is higher than the DC component alarm threshold, it indicates that the cable insulation layer is aged, damaged, damp, or has insulation defects such as water dendrites and electrical dendrites, and the preliminary diagnosis result is determined to be abnormal. Only when the cable temperature data is not higher than the temperature alarm threshold, and the DC component is not higher than the DC component alarm threshold, the preliminary diagnosis result is determined to be that the cable is normal.

[0030] Furthermore, when the initial diagnosis result of the cable is abnormal, a secondary diagnosis of the cable is performed based on the diagnosis confirmation parameters to determine the diagnosis result of the cable, wherein the secondary diagnosis of the cable is used to perform a more detailed and in-depth fault diagnosis of the cable. There are many specific implementation methods for the secondary diagnosis of the cable, which are no longer limited in the embodiments of the present application. In one achievable method, feature extraction is performed based on the partial discharge signal to determine the partial discharge feature, and abnormal discharge detection is performed based on the partial discharge feature to determine the abnormal discharge detection result, wherein the abnormal discharge detection result includes: whether there is abnormal discharge and the severity level of abnormal discharge; dielectric loss calculation is performed based on the cable current data and the cable voltage data to determine the dielectric loss factor and the loss tangent; the standard dielectric loss factor and the standard loss tangent are obtained, and dielectric loss test diagnosis is performed based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent to determine the cable insulation performance diagnosis result, wherein the cable insulation performance diagnosis result includes: good insulation performance and abnormal insulation performance; the abnormal discharge detection result and the cable insulation performance diagnosis result are combined to determine the cable diagnosis result.

[0031] Step S103: When the cable diagnosis result is abnormal, perform an insulation resistance test to collect the insulation resistance value, select a fault detection operation based on the insulation resistance value, determine a target fault detection operation, and perform a fault detection operation on the cable according to the target fault detection operation.

[0032] For the embodiments of the present application, when the cable diagnosis result is that an abnormality exists, it indicates that the cable is currently in an abnormal state. In order to more accurately know the fault type and fault location of the cable, it is necessary to perform a fault detection operation on the cable. However, different fault types and locations may require different detection methods, and the insulation resistance value can provide an important basis for selecting a suitable detection method, so as to select the most appropriate fault detection operation.

[0033] Specifically, when the cable diagnosis result is that there is an abnormality, an insulation resistance test is performed and the insulation resistance value in the test is collected. The insulation resistance test can select a traditional test method or an online monitoring method. In this regard, the embodiment of the present application is no longer limited, as long as the insulation resistance value corresponding to the cable can be collected. In a traditional insulation resistance test, it is usually necessary to power off the cable under test and use an insulation resistance tester (such as a megohmmeter) to measure the insulation resistance of the cable, that is, a certain DC voltage is applied to the cable under test, and the leakage current through the insulation layer is measured to calculate the insulation resistance value. With the development of modern electronic technology and automation technology, some special insulation resistance test instruments have been able to realize online monitoring of insulation resistance values, that is, the insulation resistance test instrument uses differential measurement technology, high impedance input circuits and advanced signal processing algorithms to eliminate or reduce the influence of the working voltage on the cable on the measurement results.

[0034] Furthermore, a fault detection operation is selected based on the insulation resistance value, a target fault detection operation is determined, and a fault detection operation is performed on the cable according to the target fault detection operation. There are many specific implementation methods for selecting the fault detection operation, and the embodiments of the present application are no longer limited. In one achievable method, the cable characteristic impedance is obtained, and the resistance value is compared based on the insulation resistance value and the cable characteristic impedance. When the insulation resistance value is greater than the cable characteristic impedance, the target fault detection operation is determined to be an impact high-voltage flashover method or a traveling wave method for fault location; when the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be a low-voltage pulse method or a DC high-voltage pulse method, wherein the cable characteristic impedance is an electrical parameter possessed by the cable, which is related to factors such as the structure, material, size, and operating frequency of the cable, and is a reference standard for judging the type of cable fault. It is generally believed that a fault resistance below several thousand ohms is a low-resistance fault, and vice versa.

[0035] Step S104: Acquire fault detection data, perform cable fault analysis based on the fault detection data, and determine the fault point location and fault type.

[0036] For the embodiment of the present application, the fault detection data that can be collected in the target fault detection operation is obtained, and the fault detection data includes but is not limited to: reflection signal, waveform characteristics, and then, the cable fault analysis is performed based on the fault detection data to determine the location of the fault point, that is, according to the propagation time of the reflection signal and the propagation speed of the signal in the cable, the location of the fault point is calculated, and at the same time, the specific type of the fault is determined in combination with the waveform characteristics and the position information, such as open circuit, short circuit, ground fault, etc. In terms of the method for determining the fault type, a morphological analysis is performed based on the waveform characteristics to observe whether the waveform is regular and whether there are abnormal fluctuations or mutations. For example, an open circuit fault may cause a significant break or missing part of the waveform; a short circuit fault may be manifested as a sudden increase in the amplitude of the waveform or an irregular waveform. At the same time, it is also necessary to measure the key parameters of the waveform, such as amplitude, phase, frequency, etc. The changes in these parameters can reflect the nature and degree of the cable fault. For example, a ground fault may cause the amplitude of the waveform to decrease, while a short circuit fault may cause the frequency of the waveform to change. Of course, when determining the fault type, the location of the fault point can also be considered comprehensively. For example, if the fault point is located at the joint of the cable, then the fault type of open circuit or poor contact is more likely; if the fault point is located at the bending part of the cable, then the fault type of insulation damage or breakage due to mechanical stress is more likely.

[0037] It can be seen that in the embodiment of the present application, the preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array are obtained, and the sensor array can cover a wider monitoring range, capture more subtle changes in the cable state, and provide richer data support for cable fault diagnosis. The cable is preliminarily diagnosed based on the preliminary diagnostic parameters. When the preliminary diagnosis result of the cable is abnormal, the cable is secondary diagnosed based on the diagnostic confirmation parameters to determine the cable diagnosis result. By combining the preliminary diagnostic parameters and the diagnostic confirmation parameters, a comprehensive assessment of the cable state can be achieved, thereby improving the accuracy of power cable diagnosis. Furthermore, when the cable diagnosis result is abnormal, an insulation resistance test is performed to collect the insulation resistance value, and a fault detection operation is selected based on the insulation resistance value, the target fault detection operation is determined, and the fault detection operation is performed on the cable according to the target fault detection operation. Finally, the fault detection data is obtained, and the cable fault analysis is performed based on the fault detection data to determine the location of the fault point and the type of fault.

[0038] Furthermore, in order to achieve a comprehensive assessment of the cable status and improve the accuracy of power cable diagnosis, in an embodiment of the present application, a secondary cable diagnosis is performed based on the diagnosis confirmation parameters to determine the cable diagnosis result, including: Extracting features based on the partial discharge signal to determine the partial discharge features, and performing abnormal discharge detection based on the partial discharge features to determine the abnormal discharge detection results, wherein the abnormal discharge detection results include: whether there is abnormal discharge and the severity level of the abnormal discharge; For the embodiment of the present application, filtering and denoising are performed based on the local discharge signal to remove the background noise in the local discharge signal, and characteristic parameters that can reflect the local discharge characteristics are extracted from the local discharge signal after filtering and denoising, such as discharge amplitude, discharge number, discharge phase, etc., and the above characteristic parameters are recorded as local discharge characteristics. Then, abnormal discharge detection is performed based on the local discharge characteristics to determine the abnormal discharge detection result, that is, the discharge amplitude threshold is pre-stored in the electronic device, when the discharge amplitude in the local discharge characteristics is greater than the discharge amplitude threshold, it is determined that the cable has abnormal discharge, otherwise, it is determined that the cable does not have abnormal discharge, wherein the discharge amplitude threshold is a threshold that can distinguish between normal discharge and abnormal discharge. Further, based on the discharge number and discharge phase in the local discharge characteristics, level analysis is performed to determine the severity level of abnormal discharge, wherein the corresponding relationship between the discharge number, discharge phase and abnormal discharge severity level is pre-stored in the electronic device, so that the abnormal discharge severity level corresponding to the local discharge can be determined quickly and accurately.

[0039] Perform dielectric loss calculation based on cable current data and cable voltage data to determine dielectric loss factor and loss tangent; Obtaining a standard dielectric loss factor and a standard loss tangent, performing dielectric loss test diagnosis based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent, and determining the cable insulation performance diagnosis result, wherein the cable insulation performance diagnosis result includes: good insulation performance and abnormal insulation performance; The cable diagnosis result is determined by combining the abnormal discharge detection results and the cable insulation performance diagnosis results.

[0040] For the embodiment of the present application, dielectric loss calculation is performed based on cable current data and cable voltage data to determine the dielectric loss factor and loss tangent. The dielectric loss factor and loss tangent are used to reflect the aging of cable insulation and are an important reference for evaluating cable insulation performance. The specific implementation process of node loss calculation is as follows: the effective value is calculated based on the collected cable current data and cable voltage data. The effective value is an important parameter of the AC signal. It indicates the DC current value when the average power generated by the signal in one cycle is equal to the power generated by the DC signal on the same resistance; then, the phase difference between the cable current data and the cable voltage data is calculated. The phase difference is a measure of the time difference between the AC signals, which reflects the phase relationship between the signals; then, according to the calculation formula of the dielectric loss factor, the effective values ​​of the voltage and current and the phase difference are substituted into the formula for calculation, where the calculation formula of the dielectric loss factor is: D = (Ic / I) * cos(φ), where D is the dielectric loss factor, Ic is the effective value of the leakage current (which can be measured by the current sensor), I is the effective value of the total current (which can be measured by the current sensor and subtracted from the leakage current), and φ is the phase difference between the voltage and the current; of course, the loss tangent can also be calculated by the following formula: D = tan(δ) * (ωC / I), where ω is the angular frequency (equal to 2π times the frequency f) and C is the capacitance of the cable (which can be measured or calculated based on the cable specifications).

[0041] After that, obtain the standard dielectric loss factor and standard loss tangent, which are determined based on the cable type, voltage level, use environment, and standards published by the International Standards Organization, and are used to evaluate the insulation performance of the cable. Of course, the user can also make small adjustments to the standard dielectric loss factor and standard loss tangent according to the actual situation. This is no longer limited in the embodiments of the present application. Then, based on the standard dielectric loss factor, standard loss tangent, dielectric loss factor, and loss tangent, dielectric loss test diagnosis is performed to determine the cable insulation performance diagnosis result, that is, if the measured dielectric loss factor and loss tangent values ​​are within the standard value range, the cable insulation performance diagnosis result is determined to be good insulation performance; otherwise, the cable insulation performance diagnosis result is determined to be abnormal insulation performance. Finally, the abnormal discharge detection result and the cable insulation performance diagnosis result are combined to determine the cable diagnosis result, that is, if any one of the abnormal discharge and insulation performance abnormality is included, the cable diagnosis result is determined to be abnormal; otherwise, the cable diagnosis result is determined to be normal. The diagnostic confirmation parameters are used to perform more detailed and in-depth fault diagnosis on the cable, so as to reveal more complex faults or defects that may exist inside the cable, achieve a comprehensive assessment of the cable status, and improve the accuracy of power cable diagnosis.

[0042] It can be seen that in the embodiment of the present application, feature extraction is performed based on the local discharge signal to determine the local discharge feature, and abnormal discharge detection is performed based on the local discharge feature to determine the abnormal discharge detection result. Then, dielectric loss calculation is performed based on the cable current data and the cable voltage data to determine the dielectric loss factor and the loss tangent, and dielectric loss test diagnosis is performed based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent to determine the cable insulation performance diagnosis result. Finally, the abnormal discharge detection result and the cable insulation performance diagnosis result are combined to determine the cable diagnosis result. The diagnostic confirmation parameters are used to perform more detailed and in-depth fault diagnosis on the cable, so as to reveal more complex faults or defects that may exist inside the cable, realize a comprehensive evaluation of the cable status, and improve the accuracy of power cable diagnosis.

[0043] Furthermore, in order to significantly improve the accuracy and efficiency of fault detection and reduce the possibility of misjudgment and missed judgment, in an embodiment of the present application, a fault detection operation is selected based on the insulation resistance value to determine a target fault detection operation, including: Obtain the cable characteristic impedance, compare the resistance value based on the insulation resistance value and the cable characteristic impedance, and when the insulation resistance value is greater than the cable characteristic impedance, determine that the target fault detection operation is the impulse high-voltage flashover method or the traveling wave method fault location; When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be the low voltage pulse method or the DC high voltage pulse method.

[0044] For the embodiments of the present application, the cable is an important component of the power system, and its failure may cause power outage or equipment damage. Through timely and accurate fault detection, the cable fault can be discovered and repaired in time to ensure the safe and stable operation of the power system. However, different fault detection methods are suitable for different fault types and resistance ranges. Therefore, selecting a suitable fault detection method can significantly improve the accuracy and efficiency of fault detection and reduce the possibility of misjudgment and missed judgment.

[0045] Specifically, the cable characteristic impedance is obtained. The cable characteristic impedance is an electrical parameter of the cable. This parameter is related to factors such as the structure, material, size and operating frequency of the cable. It is a reference standard for judging the type of cable fault, that is, when it is greater than the cable characteristic impedance, it indicates the presence of a high-resistance fault; when it is less than the cable characteristic impedance, it indicates the presence of a low-resistance fault. Then, the resistance value is compared based on the insulation resistance value and the cable characteristic impedance. When the insulation resistance value is greater than the cable characteristic impedance, the target fault detection operation is determined to be the impact high-voltage flashover method or the traveling wave method fault location. Preferably, when the field conditions of the cable are good, the more accurate and efficient traveling wave method fault location method is selected; when the field conditions of the cable are bad, the more adaptable impact high-voltage flashover method is selected. High-resistance faults are usually manifested as high equivalent impedance at the fault point, close to or equal to the cable characteristic impedance, resulting in a small reflection coefficient, which is difficult to accurately measure by conventional test methods. However, the impact high-voltage flashover method is suitable for the presence of high-resistance faults in the cable, and has a high recognition rate and accuracy; at the same time, the traveling wave method fault location is not affected by line parameters, system operation mode and fault type, and has higher reliability and accuracy.

[0046] When the insulation resistance value is less than the characteristic impedance of the cable, the target fault detection operation is determined to be the low-voltage pulse method or the DC high-voltage pulse method. Low-resistance faults are usually manifested as a significant decrease in the insulation resistance value of the cable, which may even be close to a short-circuit state. This fault will cause a significant shunting of the current near the fault point, thereby affecting the normal transmission performance of the cable. However, the low-voltage pulse method has the advantages of simple operation, fast test speed, and no damage to the cable. It is suitable for detecting low-resistance faults because these faults will cause obvious signal reflections; at the same time, in some cases, the electromagnetic interference around the cable may affect the accuracy of the low-voltage pulse method. In order to overcome the electromagnetic interference around the cable and improve the accuracy of fault detection, the DC high-voltage pulse method is selected. Among them, the DC high-voltage pulse method is based on the low-voltage pulse method. By applying a higher voltage to enhance the propagation ability and penetration of the pulse signal, the accuracy of cable fault detection is improved.

[0047] It can be seen that in the embodiments of the present application, since different fault detection methods are applicable to different fault types and resistance ranges, selecting a suitable fault detection method can significantly improve the accuracy and efficiency of fault detection and reduce the possibility of misjudgment and missed judgment. Therefore, the cable characteristic impedance is obtained, and the resistance value is compared based on the insulation resistance value and the cable characteristic impedance. When the insulation resistance value is greater than the cable characteristic impedance, the target fault detection operation is determined to be the impact high-voltage flashover method or the traveling wave method fault location. When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be the low-voltage pulse method or the DC high-voltage pulse method.

[0048] Further, in order to improve the reliability of the power cable, in the embodiment of the present application, after performing cable fault analysis based on the fault detection data and determining the fault point location and fault type, it also includes: The fault point location and the fault type are stored in the cable fault database, wherein the cable fault data of different areas are stored in different partitions in the cable fault database according to the fault point location; When a cable quality assessment instruction carrying a cable laying area is detected, based on the cable laying area in the cable quality assessment instruction, cable fault data is screened in a cable fault database to determine target cable fault data; Perform cable health assessment based on target cable fault data and generate a cable health assessment report.

[0049] For the embodiment of the present application, in order to establish a complete and systematic cable fault history record, the fault point location and fault type are stored in the cable fault database to provide data support for subsequent fault analysis, prevention and maintenance. At the same time, a cable health assessment is performed based on the cable fault data of the screened specific area, which helps to timely understand the health status of the cable, and then perform preventive maintenance to reduce the probability of failure, so as to improve the reliability of the power cable.

[0050] Specifically, the location of the fault point and the fault type are stored in the cable fault database. A database partitioning strategy is pre-established in the cable fault database so that the cable data can be partitioned and stored according to the geographical location or administrative area, which is helpful for the subsequent comprehensive evaluation of the working conditions of cables in different areas. When a cable quality assessment instruction carrying a cable laying area is detected, the cable fault data is screened in the cable fault database based on the cable laying area in the cable quality assessment instruction to determine the target cable fault data, that is, the cable laying area in the cable quality assessment instruction is used as a query condition for fault data screening, so that multiple cable fault data in the cable laying area can be screened out from the cable fault database.

[0051] Furthermore, a cable health assessment is performed based on the target cable fault data corresponding to the cable laying area, and a cable health assessment report is generated, wherein the target cable fault data can be one, two or more fault data, and the number of cable fault data is no longer limited in the embodiment of the present application. There are many specific evaluation criteria for cable health assessment, and users can set them according to actual conditions. In an achievable method, the total length of the cable corresponding to the cable laying area is obtained, and the cable health index is calculated based on the total length of the cable, the number of faults in the target cable fault data, and the type of fault, and the health index is determined, wherein the health index includes but is not limited to: failure rate, fault type distribution and fault severity index, wherein the failure rate represents the frequency of failure of a unit length of cable, and the calculation method is: failure rate = number of faults / total length of cable; the fault type distribution shows the proportion of different types of faults in cable faults, which is used to count the number of each type of fault and calculate its proportion of the total number of faults; according to the type of fault and its impact on cable performance and safety, a severity level is assigned to each fault, and then a weighted average is calculated, which is recorded as the fault severity index. Finally, the cable health assessment report is generated by combining the failure rate, fault type distribution and fault severity index.

[0052] It can be seen that in the embodiment of the present application, the fault point location and fault type are stored in the cable fault database. When a cable quality assessment instruction carrying a cable laying area is detected, the cable fault data is screened in the cable fault database based on the cable laying area in the cable quality assessment instruction to determine the target cable fault data. Then, a cable health assessment is performed based on the target cable fault data to generate a cable health assessment report. Performing a cable health assessment helps to timely understand the health status of the cable, and then perform preventive maintenance to reduce the probability of failure, so as to improve the reliability of the power cable.

[0053] Furthermore, in order to achieve accurate diagnosis of cable overheating faults and avoid false alarms and missed alarms, in the embodiment of the present application, after obtaining the preliminary diagnostic parameters collected by the sensor array, the following is also included: Perform cable heating diagnosis based on the cable temperature data in the preliminary diagnosis parameters and determine the cable heating diagnosis result; When the cable heating diagnosis result is that the cable is overheated, the overheat decomposition gas data collected by the gas sensor is obtained, and the overheat level analysis is performed based on the overheat decomposition gas data to determine the cable overheat level.

[0054] For the embodiments of the present application, overheating of the cable may lead to thermal breakdown of the insulation, causing phase-to-phase short circuit tripping, and even fire, posing a serious threat to the safe operation of the power system. However, traditional cable temperature detection methods, such as thermocouples, distributed optical fibers, and infrared thermal imaging, have problems such as small temperature measurement range, high cost, and blind spots in vision, which make it difficult to meet the overheating fault diagnosis needs of massive medium and low voltage cables. Therefore, in the power cable diagnosis method, a superimposed gas sensor is used to collect and analyze overheated decomposition gases, so that accurate diagnosis of cable overheating faults can be achieved without direct contact with the cable, avoiding false alarms and missed alarms.

[0055] Specifically, the cable temperature threshold pre-stored in the electronic device is obtained, and the cable heating diagnosis is performed based on the cable temperature threshold and the cable temperature data in the preliminary diagnostic parameters. When the cable temperature data is greater than the cable temperature threshold, the cable heating diagnosis result is determined to be cable overheating; otherwise, the cable heating diagnosis result is determined to be normal cable temperature. Furthermore, in the power cable system, a gas sensor is pre-deployed, which can monitor the decomposition gas generated when the cable is heated in real time and send it to the electronic device by wireless transmission, so that the electronic device can receive the overheating decomposition gas data of the cable in time, wherein the overheating decomposition gas data includes but is not limited to: gas type and gas concentration. Then, based on the overheating decomposition gas data, an overheating level analysis is performed to determine the overheating level of the cable. The overheating level of the cable is divided into three categories: normal, early warning, and alarm. The specific implementation method for the overheating level analysis is as follows: when the cable is operating normally and the temperature does not exceed 90°C, the amount of gas generated by the decomposition of the insulating material is relatively small, and it is mainly composed of some low-boiling volatile organic compounds (VOCs). Therefore, when the gas concentration in the overheating decomposition gas data is low and the gas type is relatively single, the cable overheating level is determined to be normal. When the cable temperature rises to between 120℃ and 160℃, the insulating material begins to decompose faster, and the types and concentrations of gases produced will increase. At this time, in addition to low-boiling-point VOCs, some higher-boiling-point compounds such as aldehydes and ketones may also be produced. Therefore, when the gas concentration in the overheated decomposition gas data reaches the gas concentration corresponding to the warning level, and the gas types include the above compounds, the cable overheating level is determined to be a warning. When the cable temperature exceeds 180℃, the decomposition rate of the insulating material will accelerate sharply, producing a large amount of high-temperature decomposition gas. These gases may contain some toxic and harmful substances, such as hydrogen (H2), methane (CH4), ethylene (C2H4), etc. In addition, some highly active free radicals and unstable compounds may be produced, which pose a serious threat to the insulation performance and safety of the cable. Therefore, when the gas types in the overheated decomposition gas data include the above toxic and harmful substances, the cable overheating level is determined to be an alarm.

[0056] It can be seen that in the embodiment of the present application, the cable heating diagnosis is performed based on the cable temperature data in the preliminary diagnostic parameters to determine the cable heating diagnosis result. When the cable heating diagnosis result is that the cable is overheated, the overheating decomposition gas data collected by the gas sensor is obtained, and the overheating level analysis is performed based on the overheating decomposition gas data to determine the cable overheating level. In the power cable diagnosis method, the superimposed gas sensor collects and analyzes the overheating decomposition gas, and the cable overheating fault is accurately diagnosed without direct contact with the cable, avoiding false alarms and missed alarms.

[0057] Further, in order to improve the accuracy and efficiency of fault location, in the embodiment of the present application, after performing cable fault analysis based on the fault detection data and determining the fault point location and fault type, it also includes: Acquire power cable network information, build a model based on the power cable network information, and obtain a three-dimensional model of the cable network; The fault visualization is performed based on the fault point location, fault type and three-dimensional model of the cable network to obtain a fault source labeled cable model, wherein the fault source labeled cable model is used to intuitively display the distribution location of the fault source in the power cable network.

[0058] For the embodiments of the present application, by constructing a three-dimensional model of the power cable network and performing a visual display in combination with the fault point location and fault type, it is helpful for fault personnel to quickly locate the fault point through an intuitive three-dimensional model, avoiding the tedious process of manual one-by-one checking in traditional methods, and greatly improving the accuracy and efficiency of fault location.

[0059] Specifically, the power cable network information is obtained from official platforms such as the power grid platform, which records the basic parameters of the cable, laying methods and connection relationships, etc. Then, the modeling tool is used to build a model based on the power cable network information to obtain a three-dimensional model of the cable network, that is, the three-dimensional path of the cable line is drawn according to the power line in the power cable network information; according to the parameter information of the cable, such as diameter, material, etc., the corresponding three-dimensional model elements are added to the cable line; the relative position relationship between the cable and other facilities, such as cable trays, cable wells, substations, etc., is considered to ensure that the cable network in the model is consistent with the actual situation; of course, the material and light and shadow effects in the modeling tool are used to enhance the realism and visualization of the model; finally, an accurate and reliable three-dimensional cable network model is obtained to provide strong support for cable management, maintenance, planning and other work.

[0060] Then, based on the fault point location, fault type and cable network 3D model, the fault visualization is performed to obtain the fault source labeled cable model, where the fault source labeled cable model is used to intuitively display the distribution of fault sources in the power cable network. Using the fault source labeled cable model, maintenance personnel can quickly locate the fault source, avoiding the tedious process of manual one-by-one investigation in traditional methods, greatly improving the accuracy and efficiency of fault location.

[0061] It can be seen that in the embodiment of the present application, the power cable network information is obtained, and the model is constructed based on the power cable network information to obtain a three-dimensional model of the cable network. Then, the fault visualization is performed based on the fault point location, fault type and cable network three-dimensional model to obtain a cable model with fault source annotation. By constructing a three-dimensional model of the power cable network and performing a visualization display in combination with the fault point location and fault type, it is helpful for fault personnel to quickly locate the fault point through an intuitive three-dimensional model, avoiding the tedious process of manual one-by-one investigation in the traditional method, and greatly improving the accuracy and efficiency of fault location.

[0062] The above embodiment introduces a power cable diagnosis method from the perspective of method flow, and the following embodiment introduces a power cable diagnosis system from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0063] The present application embodiment provides a power cable diagnostic system, such as Figure 2 As shown, the power cable diagnostic system may specifically include: The parameter acquisition module 210 is used to acquire the preliminary diagnosis parameters and diagnosis confirmation parameters collected by the sensor array, wherein the preliminary diagnosis parameters include: cable temperature data and DC component; the diagnosis confirmation parameters include: partial discharge signal, cable current data and cable voltage data; The cable diagnosis module 220 is used to perform a preliminary diagnosis of the cable based on the preliminary diagnosis parameters. When the preliminary diagnosis result of the cable is abnormal, a secondary diagnosis of the cable is performed based on the diagnosis confirmation parameters to determine the diagnosis result of the cable; A detection operation selection module 230 is used to perform an insulation resistance test to collect an insulation resistance value when the cable is diagnosed to be abnormal, select a fault detection operation based on the insulation resistance value, determine a target fault detection operation, and perform a fault detection operation on the cable according to the target fault detection operation; The fault analysis module 240 is used to obtain fault detection data, perform cable fault analysis based on the fault detection data, and determine the location of the fault point and the fault type.

[0064] For the embodiment of the present application, the preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array are obtained. The sensor array can cover a wider monitoring range, capture more subtle changes in the cable status, and provide richer data support for cable fault diagnosis. The cable is preliminarily diagnosed based on the preliminary diagnostic parameters. When the preliminary diagnostic result of the cable is abnormal, the cable is secondary diagnosed based on the diagnostic confirmation parameters to determine the cable diagnosis result. By combining the preliminary diagnostic parameters and the diagnostic confirmation parameters, a comprehensive assessment of the cable status can be achieved, thereby improving the accuracy of power cable diagnosis. Furthermore, when the cable diagnosis result is abnormal, an insulation resistance test is performed to collect the insulation resistance value, and a fault detection operation is selected based on the insulation resistance value, the target fault detection operation is determined, and the fault detection operation is performed on the cable according to the target fault detection operation. Finally, the fault detection data is obtained, and the cable fault analysis is performed based on the fault detection data to determine the fault point location and fault type.

[0065] In a possible implementation of the embodiment of the present application, the cable diagnosis module 220, when performing secondary cable diagnosis based on the diagnosis confirmation parameters to determine the cable diagnosis result, is used to: Extracting features based on the partial discharge signal to determine the partial discharge features, and performing abnormal discharge detection based on the partial discharge features to determine the abnormal discharge detection results, wherein the abnormal discharge detection results include: whether there is abnormal discharge and the severity level of the abnormal discharge; Perform dielectric loss calculation based on cable current data and cable voltage data to determine dielectric loss factor and loss tangent; Obtaining a standard dielectric loss factor and a standard loss tangent, performing dielectric loss test diagnosis based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent, and determining the cable insulation performance diagnosis result, wherein the cable insulation performance diagnosis result includes: good insulation performance and abnormal insulation performance; The cable diagnosis result is determined by combining the abnormal discharge detection results and the cable insulation performance diagnosis results.

[0066] In a possible implementation of the embodiment of the present application, when the detection operation selection module 230 performs fault detection operation selection based on the insulation resistance value and determines the target fault detection operation, it is used to: Obtain the cable characteristic impedance, compare the resistance value based on the insulation resistance value and the cable characteristic impedance, and when the insulation resistance value is greater than the cable characteristic impedance, determine that the target fault detection operation is the impulse high-voltage flashover method or the traveling wave method fault location; When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be the low voltage pulse method or the DC high voltage pulse method.

[0067] In a possible implementation of the embodiment of the present application, the power cable diagnostic system further includes: A health assessment module, used to store the fault point location and fault type in a cable fault database, wherein the cable fault data of different areas in the cable fault database are stored in different partitions according to the fault point location; When a cable quality assessment instruction carrying a cable laying area is detected, based on the cable laying area in the cable quality assessment instruction, cable fault data is screened in a cable fault database to determine target cable fault data; Perform cable health assessment based on target cable fault data and generate a cable health assessment report.

[0068] In a possible implementation of the embodiment of the present application, the power cable diagnostic system further includes: An overheating level analysis module is used to perform cable heating diagnosis based on the cable temperature data in the preliminary diagnosis parameters and determine the cable heating diagnosis result; When the cable heating diagnosis result is that the cable is overheated, the overheat decomposition gas data collected by the gas sensor is obtained, and the overheat level analysis is performed based on the overheat decomposition gas data to determine the cable overheat level.

[0069] In a possible implementation of the embodiment of the present application, the power cable diagnostic system further includes: A fault display module is used to obtain power cable network information, build a model based on the power cable network information, and obtain a three-dimensional model of the cable network; The fault visualization is performed based on the fault point location, fault type and three-dimensional model of the cable network to obtain a fault source labeled cable model, wherein the fault source labeled cable model is used to intuitively display the distribution location of the fault source in the power cable network.

[0070] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the power cable diagnostic system described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0071] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0072] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0073] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but it does not mean that there is only one bus or only one type of bus.

[0074] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0075] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0076] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0077] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0078] The embodiment of the present application provides a computer program product, which includes a computer program, and the computer program is executed by a processor to implement the method in any of the above embodiments. Compared with the related art, the embodiment of the present application obtains the preliminary diagnosis parameters and diagnosis confirmation parameters collected by the sensor array, and the sensor array can cover a wider monitoring range, capture more subtle cable state changes, and provide richer data support for cable fault diagnosis. Based on the preliminary diagnosis parameters, the cable is preliminarily diagnosed. When the preliminary diagnosis result of the cable is abnormal, the cable is secondary diagnosed based on the diagnosis confirmation parameters to determine the cable diagnosis result. By combining the preliminary diagnosis parameters and the diagnosis confirmation parameters, a comprehensive assessment of the cable state can be achieved, and the accuracy of power cable diagnosis is improved. Furthermore, when the cable diagnosis result is abnormal, an insulation resistance test is performed to collect the insulation resistance value, and a fault detection operation is selected based on the insulation resistance value, a target fault detection operation is determined, and a fault detection operation is performed on the cable according to the target fault detection operation. Finally, the fault detection data is obtained, and the cable fault analysis is performed based on the fault detection data to determine the fault point location and fault type.

[0079] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0080] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A power cable diagnostic method, characterized in that: include: Acquire preliminary diagnostic parameters and diagnostic confirmation parameters collected by the sensor array, wherein the preliminary diagnostic parameters include: cable temperature data and DC component; the diagnostic confirmation parameters include: partial discharge signal, cable current data and cable voltage data; Performing a preliminary diagnosis of the cable based on the preliminary diagnosis parameters, and when the preliminary diagnosis result of the cable is abnormal, performing a secondary diagnosis of the cable based on the diagnosis confirmation parameters to determine a confirmed result of the cable; When the cable is diagnosed as abnormal, an insulation resistance test is performed to collect an insulation resistance value, a fault detection operation is selected based on the insulation resistance value, a target fault detection operation is determined, and a fault detection operation is performed on the cable according to the target fault detection operation; Fault detection data is acquired, and cable fault analysis is performed based on the fault detection data to determine the location of the fault point and the type of fault.

2. The power cable diagnostic method according to claim 1, characterized in that: The performing secondary diagnosis of the cable based on the diagnosis confirmation parameter to determine the cable diagnosis result includes: Extracting features based on the partial discharge signal to determine partial discharge features, and performing abnormal discharge detection based on the partial discharge features to determine abnormal discharge detection results, wherein the abnormal discharge detection results include: whether abnormal discharge exists and the severity level of abnormal discharge; Performing dielectric loss calculation based on the cable current data and the cable voltage data to determine a dielectric loss factor and a loss tangent; Obtaining a standard dielectric loss factor and a standard loss tangent, performing dielectric loss test diagnosis based on the standard dielectric loss factor, the standard loss tangent, the dielectric loss factor and the loss tangent, and determining a cable insulation performance diagnosis result, wherein the cable insulation performance diagnosis result includes: good insulation performance and abnormal insulation performance; The abnormal discharge detection result and the cable insulation performance diagnosis result are combined to determine the cable diagnosis result.

3. The power cable diagnosis method according to claim 1, characterized in that: The selecting of a fault detection operation based on the insulation resistance value to determine a target fault detection operation includes: Acquire the cable characteristic impedance, compare the resistance values ​​based on the insulation resistance value and the cable characteristic impedance, and when the insulation resistance value is greater than the cable characteristic impedance, determine that the target fault detection operation is an impulse high-voltage flashover method or a traveling wave method fault location; When the insulation resistance value is less than the cable characteristic impedance, the target fault detection operation is determined to be a low voltage pulse method or a DC high voltage pulse method.

4. The power cable diagnosis method according to claim 1, characterized in that: After performing cable fault analysis based on the fault detection data and determining the fault point location and fault type, the method further includes: The fault point location and the fault type are stored in a cable fault database, wherein the cable fault data of different areas are stored in different partitions in the cable fault database according to the fault point location; When a cable quality assessment instruction carrying a cable laying area is detected, based on the cable laying area in the cable quality assessment instruction, cable fault data is screened in the cable fault database to determine target cable fault data; A cable health assessment is performed based on the target cable fault data to generate a cable health assessment report.

5. The power cable diagnosis method according to claim 1, characterized in that: After obtaining the preliminary diagnostic parameters collected by the sensor array, the method further includes: Perform cable heating diagnosis based on the cable temperature data in the preliminary diagnostic parameters, and determine the cable heating diagnosis result; When the cable heating diagnosis result is that the cable is overheated, overheat decomposition gas data collected by the gas sensor is obtained, and an overheat level analysis is performed based on the overheat decomposition gas data to determine the cable overheat level.

6. The power cable diagnosis method according to claim 1, characterized in that: After performing cable fault analysis based on the fault detection data and determining the fault point location and fault type, the method further includes: Acquire power cable network information, and construct a model based on the power cable network information to obtain a three-dimensional model of the cable network; A fault visualization display is performed based on the fault point location, the fault type and the cable network three-dimensional model to obtain a fault source labeled cable model, wherein the fault source labeled cable model is used to intuitively display the distribution location of the fault source in the power cable network.

7. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the power cable diagnostic method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the power cable diagnosis method according to any one of claims 1 to 6.

9. A computer program product, characterized in that The method comprises a computer program, wherein the computer program is executed by a processor to perform the power cable diagnosis method according to any one of claims 1 to 6.

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