A high-voltage cable fault monitoring method based on built-in wireless passive sensor

Abstract

The present invention belongs to the field of smart grid monitoring technology and relates to a high-voltage cable fault monitoring method based on a built-in wireless passive sensor. First, each target high-voltage cable segment is accurately located by a discharge induction coil arranged on the target high-voltage cable. By means of a detailed analysis of the frequency, waveform regularity and intensity of the pulse signal, it is accurately determined whether there is a local discharge phenomenon in each target high-voltage cable segment. Once the local discharge phenomenon is detected, a more in-depth fault risk verification is performed on the potential fault high-voltage cable segment. That is, the built-in wireless passive sensor is used to monitor relevant information. This not only effectively solves the limitations of traditional wired monitoring equipment in terms of flexibility and low accuracy, but also reasonably evaluates the fault risk estimation index of each potential fault high-voltage cable segment from the perspective of mechanical deformation, temperature anomaly and comprehensive power performance, which helps to provide early warning and intervention in the early stage of the fault, thereby avoiding or reducing the losses caused by the fault.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart grid monitoring and relates to a high-voltage cable fault monitoring method based on a built-in wireless passive sensor. Background Art

[0002] With the acceleration of urbanization, electricity demand continues to grow. As the primary carrier of urban power supply, the safety and stability of high-voltage cables are crucial to their normal operation. However, due to the complex environment of underground cable tunnels, high-voltage cables may encounter various faults during operation, such as overloads, short circuits, and insulation aging. These faults can not only cause power outages but also lead to safety accidents such as fires. Therefore, real-time fault monitoring and early warning of high-voltage cables in underground cable tunnels are of great practical significance.

[0003] Existing high-voltage cable fault monitoring methods have circumvented the defects of traditional manual inspections and offline monitoring, which are highly subjective and have low real-time benefits. Online monitoring equipment is used to sense high-voltage cable power information in real time for fault troubleshooting. Although this method meets existing requirements, it still has certain limitations, which are specifically manifested in the following aspects:

[0004] 1. Existing methods can often only detect fault signals or abnormal conditions after a certain degree of fault occurs in the high-voltage cable, resulting in a lag in monitoring and diagnosis. They fail to effectively capture the key information that partial discharge is a precursor to fault occurrence, making it impossible to timely estimate the fault risk as early as possible in the early stage of the fault, limiting the ability to respond to potential faults quickly and accurately. In addition, although some existing methods can detect the occurrence of partial discharge and issue early warnings, the presence of partial discharge does not mean that a fault will definitely occur. Therefore, there is often a lack of comprehensive verification of the fault risk of the high-voltage cable segment where the partial discharge phenomenon occurs, which is not conducive to the reasonable and accurate feedback of fault monitoring results.

[0005] 2. Existing methods of high-voltage cable monitoring equipment mostly adopt wired deployment, which is restricted and affected by the monitoring environment and requires additional power supply, which may lead to higher power consumption and maintenance costs. It is not flexible, convenient, scalable and low-cost at the deployment level. At the data monitoring level, it mostly monitors from the outside to the inside, and the acquisition of the internal state of the high-voltage cable may not be accurate enough. For example, the external mechanical damage of the high-voltage cable is mostly limited to the physical visible damage on the surface of the high-voltage cable. It is difficult to detect tiny or hidden damage in the insulation layer, which may lead to a decrease in the accuracy of identifying and predicting potential problems, affecting the effect of fault detection. Summary of the Invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a high-voltage cable fault monitoring method based on a built-in wireless passive sensor is proposed.

[0007] The purpose of the present invention is achieved through the following technical solutions:

[0008] A high-voltage cable fault monitoring method based on a built-in wireless passive sensor, comprising:

[0009] S1. Target high-voltage cable division: A high-voltage cable laid in an underground cable tunnel is recorded as the target high-voltage cable. Based on the positions of the discharge induction coils arranged in the target high-voltage cable, the target high-voltage cable is divided into cable segments, which are recorded as target high-voltage cable segments.

[0010] S2. Determination of partial discharge phenomenon: each target high-voltage cable segment is matched with each discharge induction coil, and the discharge induction coil is used to monitor the induced pulse information of the target high-voltage cable segment in real time to determine whether there is a partial discharge phenomenon in each target high-voltage cable segment;

[0011] S3. Fault risk estimation instruction trigger: The target high-voltage cable segments with partial discharge phenomena are recorded as potential fault high-voltage cable segments, and the discharge induction coil of each potential fault high-voltage cable segment triggers the fault risk estimation instruction;

[0012] S4. Screening of Warning Fault High-Voltage Cable Segments: Receives a fault risk estimation instruction, collects and analyzes monitoring information from built-in sensors of each potential fault high-voltage cable segment, obtains a fault risk estimation index for each potential fault high-voltage cable segment, and further screens out each warning fault high-voltage cable segment;

[0013] S5. Warning fault high-voltage cable section feedback: Fault warning feedback is provided for each warning fault high-voltage cable section.

[0014] Preferably, the induction pulse information includes the frequency range, amplitude and waveform curve of each pulse signal received within a set time period.

[0015] Preferably, the determination of whether there is a partial discharge phenomenon in each target high-voltage cable segment includes: extracting the frequency interval of each pulse signal received within a set time period from the induced pulse information of each target high-voltage cable segment, comparing it with the specific frequency interval of the partial discharge signal stored in the WEB cloud, and obtaining the number m of overlapping frequencies of each pulse signal received within the set time period of each target high-voltage cable segment. ij and the integer frequency number m of the specific frequency interval of the partial discharge signal 整 , where i is the number of each target high-voltage cable segment, i = 1, 2, ..., a, j is the number of each pulse signal received within the set time period, j = 1, 2, ..., b, according to the formula The frequency matching degree of the pulse signal of each target high-voltage cable segment is obtained, where b is the number of pulse signals received within the set time period.

[0016] The waveform curves of each pulse signal received within a set time period are extracted from the induced pulse information of each target high-voltage cable segment, and the waveform curves of each pulse signal received within a set time period of a target high-voltage cable segment are sequentially imported into the same coordinate system of the CAD software. The waveform curve lengths of each pulse signal received within the set time period of the target high-voltage cable segment are respectively obtained, and the average waveform curve length of the pulse signal of the target high-voltage cable segment is calculated.

[0017] After all the waveform curves of the pulse signals received within the set time period of the target high-voltage cable segment are imported into the same coordinate system of the CAD software, a superposition analysis is performed to obtain the overall waveform overlap curve length of the target high-voltage cable pulse signal.

[0018] The ratio of the overall waveform coincidence curve length to the average waveform curve length is used as the waveform regularity matching degree of the target high-voltage cable segment pulse signal, and then the waveform regularity matching degree β of the pulse signal of each target high-voltage cable segment is obtained. i .

[0019] Extract the amplitude v of each pulse signal received within a set time period from the induction pulse information of each target high-voltage cable segment ij , combined with the preset partial discharge signal amplitude threshold v0 stored in the WEB cloud, the intensity coefficient χ of the pulse signal of each target high-voltage cable segment is analyzed i , and its calculation formula is:

[0020]

[0021] where v i(j-1) The amplitude of the j-1th pulse signal received within the time period is set for the i-th target high-voltage cable segment;

[0022] Then by the formula The comprehensive matching degree of the pulse signal of each target high-voltage cable segment is obtained, where e is a natural constant.

[0023] Preferably, the determination of whether there is a partial discharge phenomenon in each target high-voltage cable segment also includes: comparing the comprehensive matching degree of the pulse signal of each target high-voltage cable segment with a preset reasonable threshold value of the comprehensive matching degree of the pulse signal; if the comprehensive matching degree of the pulse signal of a target high-voltage cable segment is greater than or equal to the preset reasonable threshold value of the comprehensive matching degree of the pulse signal, then it is determined that there is a partial discharge phenomenon in the target high-voltage cable segment; otherwise, it is determined that there is no partial discharge phenomenon in the target high-voltage cable segment, thereby obtaining a determination result of whether there is a partial discharge phenomenon in each target high-voltage cable segment.

[0024] Preferably, the built-in sensor monitoring information includes fiber Bragg grating sensor monitoring information, fiber temperature sensor monitoring information and fiber power sensor monitoring information.

[0025] The monitoring information of the fiber Bragg grating sensor includes the maximum distance change value and the maximum stress change value between each conductive core and the fiber Bragg grating sensor layout point within a set time period.

[0026] The monitoring information of the optical fiber temperature sensor includes the average temperature value and the maximum temperature gradient value at each monitoring time point within the set time period.

[0027] The monitoring information of the optical fiber power sensor includes the voltage monitoring waveform and the current monitoring waveform of each optical fiber power sensor deployment point within a set time period.

[0028] Preferably, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment includes: extracting the maximum distance change value Δd between each conductive core and the fiber Bragg grating sensor deployment point within a set time period from the fiber Bragg grating sensor monitoring information of each potential fault high-voltage cable segment. i′c and the maximum stress change Δf i′c , where i′ is the number of each potential fault high-voltage cable segment, i′=1, 2, ..., a′, c is the number of each conductive core, c=1, 2, ..., h, and the reference distance d between the fiber Bragg grating sensor deployment point and each conductive cable is set when the fiber Bragg grating sensor is initially deployed in each potential fault high-voltage cable segment stored in the WEB cloud. i ″ c and reference stress value f′ i′c , analyze the mechanical deformation coefficient λ of each potential fault high-voltage cable segment i′ , and its calculation formula is:

[0029]

[0030] Preferably, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment further includes: extracting the average temperature value of each monitoring time point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment and the maximum temperature gradient Δw i′z , where z is the number of each monitoring time point in the set time period, z = 1, 2, ..., l. Combined with the reasonable working temperature threshold w0 of the high-voltage cable and the reasonable temperature distribution gradient threshold Δw0 stored in the WEB cloud, the temperature anomaly degree coefficient t of each potential fault high-voltage cable segment is analyzed. i′ , and its calculation formula is:

[0031]

[0032] Where l is the number of monitoring time points within the set time period.

[0033] Preferably, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment further includes: extracting the voltage monitoring waveform of each optical fiber power sensor deployment point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment, and obtaining the voltage peak value of each optical fiber power sensor deployment point within a set time period of each potential fault high-voltage cable segment. Voltage valley And the voltage value at each unit time point Where q is the number of each fiber optic power sensor deployment point, q = 1, 2, ..., p, n is the number of each unit time point in the set time period, n = 1, 2, ..., k, calculate the voltage effective value of each fiber optic power sensor deployment point in the set time period of each potential fault high-voltage cable section. k is the number of unit time points in the set time period. Combined with the output voltage value U0 of the target high-voltage cable stored in the WEB cloud, the power transmission status evaluation coefficient ψ of each potential fault high-voltage cable segment is analyzed. i′ , and its calculation formula is:

[0034]

[0035] p is the number of fiber optic power sensor deployment points.

[0036] Extract the current monitoring waveform of each fiber optic power sensor deployment point within the set time period from the fiber optic temperature sensor monitoring information of each potential fault high-voltage cable section, and obtain the current value of each fiber optic power sensor deployment point at each unit time point within the set time period of each potential fault high-voltage cable section Analyze the load state evaluation coefficient r of each potential fault high-voltage cable segment i′ , and its calculation formula is:

[0037]

[0038] Where ΔI is the preset reasonable current fluctuation threshold of the high-voltage cable between adjacent time points stored in the WEB cloud. The current value of the n-1th time unit point at the qth fiber optic power sensor deployment point within the time period is set for the i′th potential fault high-voltage cable segment.

[0039] By the formula The comprehensive power performance coefficient of each potential fault high-voltage cable section is obtained.

[0040] Preferably, the calculation formula for the failure risk prediction index of each potential fault high-voltage cable segment is: in The corresponding weight ratios of the preset mechanical deformation coefficient, temperature anomaly coefficient, and power comprehensive performance coefficient.

[0041] Preferably, the screening out of each warning fault high-voltage cable segment includes: comparing the fault risk prediction index of each potential fault high-voltage cable segment with a preset reasonable threshold value of the high-voltage cable segment fault risk prediction index; if the fault risk prediction index of a potential fault high-voltage cable segment is greater than or equal to the preset reasonable threshold value of the high-voltage cable segment fault risk prediction index, then the potential fault high-voltage cable segment is recorded as a warning fault high-voltage cable segment, thereby screening out each warning fault high-voltage cable segment.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention divides the target high-voltage cable into cable segments according to the positions of the discharge induction coils arranged on the target high-voltage cable, performs fault monitoring on the target high-voltage cable segments, effectively improves the efficiency of fault detection, helps to quickly determine the specific segment where the fault is located, and facilitates accurate repair and maintenance.

[0043] (2) The present invention utilizes a discharge induction coil to monitor the induced pulse information of the target high-voltage cable segment in real time, and realizes high-precision detection of the local discharge phenomenon of the target high-voltage cable segment from three perspectives: frequency matching, waveform matching and intensity coefficient of the pulse signal, thereby improving the scientificity, reliability and accuracy of the determination results of whether there is a local discharge phenomenon in each target high-voltage cable segment, and laying the foundation for the subsequent fault risk prediction index analysis.

[0044] (3) The present invention collects analytical parameters of the fault risk prediction index of each potential fault high-voltage cable segment based on the built-in wireless passive sensors, namely, fiber optic Bragg grating sensors, fiber optic temperature sensors and fiber optic power sensors, of each potential fault high-voltage cable segment, thereby avoiding the problems of lack of flexibility, convenience, scalability and low cost of wired monitoring equipment, thereby significantly improving the efficiency and accuracy of high-voltage cable fault monitoring.

[0045] (4) The present invention uses the relevant information monitored by the built-in wireless passive sensor to comprehensively evaluate the fault risk prediction index of each potential fault high-voltage cable segment from the mechanical deformation degree coefficient, temperature anomaly degree coefficient, and power comprehensive performance coefficient. Based on the internal multi-dimensional parameters of each potential fault high-voltage cable segment, the health status and potential fault risk of the cable are comprehensively reflected. After the partial discharge phenomenon exists, the failure risk possibility of each potential fault high-voltage cable segment is further verified, which helps to provide early warning and intervention in the early stage of the fault, thereby avoiding or reducing the losses caused by the fault. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] 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. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 This is a flow chart of a high-voltage cable fault monitoring method based on a built-in wireless passive sensor according to an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the layout of the fiber Bragg grating sensor according to an embodiment of the present invention.

[0049] Figure numerals: 1. Fiber Bragg grating sensor installation point. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] See also Figure 1 As shown, an embodiment of the present invention provides a high-voltage cable fault monitoring method based on a built-in wireless passive sensor, comprising the following steps:

[0052] S1. Target high-voltage cable division: A high-voltage cable laid in an underground cable tunnel is recorded as a target high-voltage cable. Based on the positions of the discharge induction coils arranged on the target high-voltage cable, the target high-voltage cable is divided into cable segments, which are recorded as target high-voltage cable segments.

[0053] The embodiment of the present invention divides the target high-voltage cable into cable segments based on the positions of the discharge induction coils arranged on the target high-voltage cable, performs fault monitoring on the target high-voltage cable segments, effectively improves the efficiency of fault detection, helps to quickly determine the specific segment where the fault is located, and facilitates accurate repair and maintenance.

[0054] S2. Determination of partial discharge phenomenon: each target high-voltage cable segment is matched with each discharge induction coil one by one, and the discharge induction coil is used to monitor the induced pulse information of the target high-voltage cable segment in real time to determine whether there is partial discharge phenomenon in each target high-voltage cable segment.

[0055] Specifically, the induction pulse information includes the frequency range, amplitude and waveform curve of each pulse signal received within a set time period.

[0056] Specifically, the determination of whether there is a partial discharge phenomenon in each target high-voltage cable segment includes: extracting the frequency interval of each pulse signal received within a set time period in the induced pulse information of each target high-voltage cable segment, comparing it with the specific frequency interval of the partial discharge signal stored in the WEB cloud, and obtaining the number m of overlapping frequencies of each pulse signal received within the set time period of each target high-voltage cable segment. ij and the integer frequency number m of the specific frequency interval of the partial discharge signal 整 , where i is the number of each target high-voltage cable segment, i = 1, 2, ..., a, j is the number of each pulse signal received within the set time period, j = 1, 2, ..., b, according to the formula The frequency matching degree of the pulse signal of each target high-voltage cable segment is obtained, where b is the number of pulse signals received within the set time period.

[0057] The waveform curves of each pulse signal received within a set time period are extracted from the induced pulse information of each target high-voltage cable segment, and the waveform curves of each pulse signal received within a set time period of a target high-voltage cable segment are sequentially imported into the same coordinate system of the CAD software. The waveform curve lengths of each pulse signal received within the set time period of the target high-voltage cable segment are respectively obtained, and the average waveform curve length of the pulse signal of the target high-voltage cable segment is calculated.

[0058] After all the waveform curves of the pulse signals received within the set time period of the target high-voltage cable segment are imported into the same coordinate system of the CAD software, a superposition analysis is performed to obtain the overall waveform overlap curve length of the target high-voltage cable pulse signal.

[0059] The ratio of the overall waveform coincidence curve length to the average waveform curve length is used as the waveform regularity matching degree of the target high-voltage cable segment pulse signal, and then the waveform regularity matching degree β of the pulse signal of each target high-voltage cable segment is obtained. i .

[0060] Extract the amplitude v of each pulse signal received within a set time period from the induction pulse information of each target high-voltage cable segment ij , combined with the preset partial discharge signal amplitude threshold v0 stored in the WEB cloud, the intensity coefficient χ of the pulse signal of each target high-voltage cable segment is analyzed i , and its calculation formula is: where v i(j-1) The amplitude of the j-1th pulse signal received within the time period is set for the i-th target high-voltage cable segment.

[0061] Then by the formula The comprehensive matching degree of the pulse signal of each target high-voltage cable segment is obtained, where e is a natural constant.

[0062] Specifically, the determination of whether there is a partial discharge phenomenon in each target high-voltage cable segment also includes: comparing the comprehensive matching degree of the pulse signal of each target high-voltage cable segment with a preset reasonable threshold value of the comprehensive matching degree of the pulse signal; if the comprehensive matching degree of the pulse signal of a target high-voltage cable segment is greater than or equal to the preset reasonable threshold value of the comprehensive matching degree of the pulse signal, then it is determined that there is a partial discharge phenomenon in the target high-voltage cable segment; otherwise, it is determined that there is no partial discharge phenomenon in the target high-voltage cable segment, thereby obtaining a determination result of whether there is a partial discharge phenomenon in each target high-voltage cable segment.

[0063] The embodiment of the present invention utilizes a discharge induction coil to monitor the induced pulse information of a target high-voltage cable segment in real time, and realizes high-precision detection of partial discharge phenomena in the target high-voltage cable segment from three perspectives: frequency consistency, waveform regularity consistency, and intensity coefficient of the pulse signal. This improves the scientificity, reliability, and accuracy of the determination results of whether partial discharge phenomena exist in each target high-voltage cable segment, laying the foundation for subsequent fault risk prediction index analysis.

[0064] S3. Fault risk prediction instruction triggering: each target high-voltage cable segment with partial discharge phenomenon is recorded as each potential fault high-voltage cable segment, and the discharge induction coil of each potential fault high-voltage cable segment triggers the fault risk prediction instruction.

[0065] S4. Screening of warning fault high-voltage cable segments: Receive fault risk prediction instructions, collect and analyze the built-in sensor monitoring information of each potential fault high-voltage cable segment, obtain the fault risk prediction index of each potential fault high-voltage cable segment, and further screen out each warning fault high-voltage cable segment.

[0066] Specifically, the built-in sensor monitoring information includes fiber grating sensor monitoring information, fiber optic temperature sensor monitoring information and fiber optic power sensor monitoring information.

[0067] The monitoring information of the fiber Bragg grating sensor includes the maximum distance change value and the maximum stress change value between each conductive core and the fiber Bragg grating sensor layout point within a set time period.

[0068] The monitoring information of the optical fiber temperature sensor includes the average temperature value and the maximum temperature gradient value at each monitoring time point within the set time period.

[0069] The monitoring information of the optical fiber power sensor includes the voltage monitoring waveform and the current monitoring waveform of each optical fiber power sensor deployment point within a set time period.

[0070] It should be noted that the above-mentioned fiber Bragg grating sensors and fiber temperature sensors are distributed sensors, which are composed of continuously distributed fiber optic sensing units of equal length. There is no spacing between adjacent sensing units, so the relevant information of each sensing segment on the entire optical fiber can be obtained. When the fiber Bragg grating sensors and fiber temperature sensors are initially deployed, the corresponding models are selected according to the length of each target high-voltage cable segment, and thus they are suitable for monitoring the information of the corresponding target high-voltage cable segment. The fiber Bragg grating sensor deployment point is located at the center of the splicing of the conductor cores inside the high-voltage cable. For details, please refer to Figure 2 shown.

[0071] It should also be noted that the above temperature gradient value refers to the maximum temperature difference between each unit line segment on the high-voltage cable segment.

[0072] It should be further explained that the above-mentioned fiber optic power sensor can monitor the voltage and current values ​​at each unit time point within the set time period at its layout location in real time, and automatically generate the voltage monitoring waveform and current monitoring waveform for the set time period. The number of fiber optic power sensors to be laid out in a single high-voltage cable segment is obtained by comprehensively considering factors such as the length, diameter, material, insulation layer thickness, number and position of the high-voltage cable segment, and the temperature and humidity of the environment, and is usually determined in advance by professional staff.

[0073] The embodiment of the present invention collects analysis parameters of the fault risk prediction index of the potential fault high-voltage cable segment based on the built-in wireless passive sensors of each potential fault high-voltage cable segment, namely, the fiber optic Bragg grating sensor, the fiber optic temperature sensor and the fiber optic power sensor, thereby avoiding the problems of lack of flexibility, convenience, scalability and low cost of wired monitoring equipment, thereby significantly improving the efficiency and accuracy of high-voltage cable fault monitoring.

[0074] Specifically, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment includes: extracting the maximum distance change value Δd between each conductive core and the fiber Bragg grating sensor deployment point within a set time period from the fiber Bragg grating sensor monitoring information of each potential fault high-voltage cable segment; i′c and the maximum stress change Δf i′c , where i′ is the number of each potential fault high-voltage cable segment, i′=1, 2, …, a′, c is the number of each conductive core, c=1, 2, …, h, and the reference distance d′ between the fiber Bragg grating sensor deployment point and each conductive cable is set when the fiber Bragg grating sensor is initially deployed in each potential fault high-voltage cable segment stored in the WEB cloud. i′c and reference stress value f′ i′c , analyze the mechanical deformation coefficient λ of each potential fault high-voltage cable segment i′ , and its calculation formula is:

[0075]

[0076] Specifically, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment also includes: extracting the average temperature value of each monitoring time point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment; and the maximum temperature gradient Δw i′z , where z is the number of each monitoring time point in the set time period, z = 1, 2, ..., l. Combined with the reasonable working temperature threshold w0 of the high-voltage cable and the reasonable temperature distribution gradient threshold Δw0 stored in the WEB cloud, the temperature anomaly degree coefficient t of each potential fault high-voltage cable segment is analyzed. i′ , and its calculation formula is:

[0077] Where l is the number of monitoring time points within the set time period.

[0078] Specifically, the analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment also includes: extracting the voltage monitoring waveform of each optical fiber power sensor deployment point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment, and obtaining the voltage peak value of each optical fiber power sensor deployment point within a set time period of each potential fault high-voltage cable segment. Voltage valley And the voltage value at each unit time point Where q is the number of each fiber optic power sensor deployment point, q = 1, 2, ..., p, n is the number of each unit time point in the set time period, n = 1, 2, ..., k, calculate the voltage effective value of each fiber optic power sensor deployment point in the set time period of each potential fault high-voltage cable section. k is the number of unit time points in the set time period. Combined with the output voltage value U0 of the target high-voltage cable stored in the WEB cloud, the power transmission status evaluation coefficient ψ of each potential fault high-voltage cable segment is analyzed. i′ , and its calculation formula is:

[0079]

[0080] p is the number of fiber optic power sensor deployment points.

[0081] Extract the current monitoring waveform of each fiber optic power sensor deployment point within the set time period from the fiber optic temperature sensor monitoring information of each potential fault high-voltage cable section, and obtain the current value of each fiber optic power sensor deployment point at each unit time point within the set time period of each potential fault high-voltage cable section Analyze the load state evaluation coefficient r of each potential fault high-voltage cable segment i′ , and its calculation formula is: Where ΔI is the preset reasonable current fluctuation threshold of the high-voltage cable between adjacent time points stored in the WEB cloud. The current value of the n-1th time unit point at the qth fiber optic power sensor deployment point within the time period is set for the i′th potential fault high-voltage cable segment.

[0082] By the formula The comprehensive power performance coefficient of each potential fault high-voltage cable section is obtained.

[0083] Specifically, the calculation formula for the fault risk estimation index of each potential fault high-voltage cable segment is: in The corresponding weight ratios of the preset mechanical deformation coefficient, temperature anomaly coefficient, and power comprehensive performance coefficient.

[0084] Specifically, the screening out of each warning fault high-voltage cable segment includes: comparing the fault risk prediction index of each potential fault high-voltage cable segment with a preset reasonable threshold value of the high-voltage cable segment fault risk prediction index; if the fault risk prediction index of a potential fault high-voltage cable segment is greater than or equal to the preset reasonable threshold value of the high-voltage cable segment fault risk prediction index, then the potential fault high-voltage cable segment is recorded as a warning fault high-voltage cable segment, and then the warning fault high-voltage cable segments are screened out.

[0085] S5. Warning fault high-voltage cable section feedback: Fault warning feedback is provided for each warning fault high-voltage cable section.

[0086] The embodiment of the present invention uses the relevant information monitored by the built-in wireless passive sensor to comprehensively evaluate the fault risk prediction index of each potential fault high-voltage cable segment from the perspective of mechanical deformation degree coefficient, temperature anomaly degree coefficient, and power comprehensive performance coefficient. Based on the internal multi-dimensional parameters of each potential fault high-voltage cable segment, the health status and potential fault risk of the cable are comprehensively reflected. After the partial discharge phenomenon exists, the failure risk possibility of each potential fault high-voltage cable segment is further verified, which helps to provide early warning and intervention in the early stage of the fault, thereby avoiding or reducing the losses caused by the fault.

[0087] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A high-voltage cable fault monitoring method based on a built-in wireless passive sensor, characterized in that: The steps include: S1. Target high-voltage cable division: A high-voltage cable laid in an underground cable tunnel is recorded as the target high-voltage cable. Based on the positions of the discharge induction coils arranged in the target high-voltage cable, the target high-voltage cable is divided into cable segments, which are recorded as target high-voltage cable segments. S2. Determination of partial discharge phenomenon: each target high-voltage cable segment is matched with each discharge induction coil, and the discharge induction coil is used to monitor the induced pulse information of the target high-voltage cable segment in real time to determine whether there is a partial discharge phenomenon in each target high-voltage cable segment; S3. Fault risk estimation instruction trigger: The target high-voltage cable segments with partial discharge phenomena are recorded as potential fault high-voltage cable segments, and the discharge induction coil of each potential fault high-voltage cable segment triggers the fault risk estimation instruction; S4. Screening of Warning Fault High-Voltage Cable Segments: Receives a fault risk estimation instruction, collects and analyzes monitoring information from built-in sensors of each potential fault high-voltage cable segment, obtains a fault risk estimation index for each potential fault high-voltage cable segment, and further screens out each warning fault high-voltage cable segment; S5. Warning fault high-voltage cable segment feedback: Fault warning feedback is provided for each warning fault high-voltage cable segment; The determination of whether there is a partial discharge phenomenon in each target high-voltage cable segment includes: extracting the frequency interval of each pulse signal received within a set time period from the induced pulse information of each target high-voltage cable segment, comparing it with the specific frequency interval of the partial discharge signal stored in the WEB cloud, and obtaining the number of overlapping frequencies of each pulse signal received within the set time period of each target high-voltage cable segment. and the integer number of frequencies in a specific frequency range of the partial discharge signal ,in is the number of each target high-voltage cable segment, , It is the number of each pulse signal received within the set time period. , according to the formula The frequency matching degree of the pulse signal of each target high-voltage cable segment is obtained, where The number of pulse signals received within the set time period; Extracting the waveform curves of each pulse signal received within a set time period from the induced pulse information of each target high-voltage cable segment, sequentially importing the waveform curves of each pulse signal received within the set time period of a target high-voltage cable segment into the same coordinate system of the CAD software, respectively obtaining the waveform curve lengths of each pulse signal received within the set time period of the target high-voltage cable segment, and calculating the average waveform curve length of the pulse signal of the target high-voltage cable segment; After all the waveform curves of the pulse signals received within the set time period of the target high-voltage cable segment are imported into the same coordinate system of the CAD software, a superposition analysis is performed to obtain the overall waveform overlap curve length of the target high-voltage cable pulse signal; The ratio of the overall waveform coincidence curve length to the average waveform curve length is used as the waveform regularity of the target high-voltage cable segment pulse signal, and then the waveform regularity of each target high-voltage cable segment pulse signal is obtained. ; Extract the amplitude of each pulse signal received within a set time period from the induction pulse information of each target high-voltage cable segment , combined with the preset partial discharge signal amplitude threshold stored in the WEB cloud , analyze the intensity coefficient of the pulse signal of each target high-voltage cable segment , and its calculation formula is: ,in For the The first target high-voltage cable segment receives the The amplitude of a pulse signal; Then by the formula The comprehensive matching degree of the pulse signal of each target high-voltage cable segment is obtained, where is a natural constant.

2. A high-voltage cable fault monitoring method based on a built-in wireless passive sensor according to claim 1, characterized in that: The induction pulse information includes the frequency range, amplitude and waveform curve of each pulse signal received within a set time period.

3. The high-voltage cable fault monitoring method based on a built-in wireless passive sensor according to claim 1 is characterized in that: The method of determining whether there is a partial discharge phenomenon in each target high-voltage cable segment further includes: comparing the comprehensive matching degree of the pulse signal of each target high-voltage cable segment with a preset reasonable threshold value of the comprehensive matching degree of the pulse signal; if the comprehensive matching degree of the pulse signal of a target high-voltage cable segment is greater than or equal to the preset reasonable threshold value of the comprehensive matching degree of the pulse signal, then it is determined that there is a partial discharge phenomenon in the target high-voltage cable segment; otherwise, it is determined that there is no partial discharge phenomenon in the target high-voltage cable segment, thereby obtaining a determination result of whether there is a partial discharge phenomenon in each target high-voltage cable segment.

4. The method for monitoring high-voltage cable faults based on a built-in wireless passive sensor according to claim 1, characterized in that: The built-in sensor monitoring information includes fiber Bragg grating sensor monitoring information, fiber temperature sensor monitoring information and fiber power sensor monitoring information; The monitoring information of the fiber Bragg grating sensor includes the maximum distance change value and the maximum stress change value between each conductive core and the fiber Bragg grating sensor deployment point within a set time period; The monitoring information of the optical fiber temperature sensor includes the average temperature value and the maximum temperature gradient value at each monitoring time point within the set time period; The monitoring information of the optical fiber power sensor includes the voltage monitoring waveform and the current monitoring waveform of each optical fiber power sensor deployment point within a set time period.

5. The method for monitoring high-voltage cable faults based on a built-in wireless passive sensor according to claim 4, characterized in that: The analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment includes: extracting the maximum distance change value between each conductive core and the fiber optic Bragg grating sensor deployment point within a set time period from the fiber optic Bragg grating sensor monitoring information of each potential fault high-voltage cable segment; and maximum stress change ,in is the number of each potential fault high voltage cable section, , is the number of each conductive core, , when initially laying out fiber grating sensors in each potential fault high-voltage cable section stored in the WEB cloud, set the reference distance between the fiber grating sensor deployment point and each conductive cable and reference stress values , analyze the mechanical deformation coefficient of each potential fault high-voltage cable segment , and its calculation formula is: .

6. The method for monitoring high-voltage cable faults based on a built-in wireless passive sensor according to claim 5, characterized in that: The analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment also includes: extracting the average temperature value of each monitoring time point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment and the maximum temperature gradient ,in It is the number of each monitoring time point within the set time period. , combined with the reasonable operating temperature threshold of high-voltage cables stored in the WEB cloud And reasonable temperature distribution gradient threshold , analyze the temperature anomaly coefficient of each potential fault high-voltage cable segment , and its calculation formula is: ,in The number of monitoring time points within the set time period.

7. The method for monitoring high-voltage cable faults based on a built-in wireless passive sensor according to claim 6, characterized in that: The analysis of the built-in sensor monitoring information of each potential fault high-voltage cable segment also includes: extracting the voltage monitoring waveform of each optical fiber power sensor deployment point within a set time period from the optical fiber temperature sensor monitoring information of each potential fault high-voltage cable segment, and obtaining the voltage peak value of each optical fiber power sensor deployment point within the set time period of each potential fault high-voltage cable segment. , voltage valley And the voltage value at each unit time point ,in is the number of each fiber optic power sensor deployment point, , It is the number of each unit time point in the set time period. , calculate the effective voltage value of each fiber optic power sensor deployment point within the set time period of each potential fault high-voltage cable section , , Set the output voltage value for the target high-voltage cable stored in the WEB cloud based on the number of unit time points within the set time period , analyze the power transmission status evaluation coefficient of each potential fault high-voltage cable section , and its calculation formula is: , The number of points for laying fiber optic power sensors; Extract the current monitoring waveform of each fiber optic power sensor deployment point within the set time period from the fiber optic temperature sensor monitoring information of each potential fault high-voltage cable section, and obtain the current value of each fiber optic power sensor deployment point at each unit time point within the set time period of each potential fault high-voltage cable section , analyze the load state evaluation coefficient of each potential fault high-voltage cable section , and its calculation formula is: ,in The preset reasonable current fluctuation threshold of the high-voltage cable between adjacent time points stored in the WEB cloud, For the The first potential fault high voltage cable section within the set time period The fiber optic power sensor installation point The current value at each unit time point; By the formula The comprehensive power performance coefficient of each potential fault high-voltage cable section is obtained.

8. The method for monitoring high-voltage cable faults based on a built-in wireless passive sensor according to claim 7, characterized in that: The calculation formula for the failure risk estimation index of each potential fault high-voltage cable segment is: ,in The corresponding weight ratios of the preset mechanical deformation coefficient, temperature anomaly coefficient, and power comprehensive performance coefficient.

9. The high-voltage cable fault monitoring method based on a built-in wireless passive sensor according to claim 8, characterized in that: The screening out of each warning fault high-voltage cable segment includes: comparing the fault risk estimation index of each potential fault high-voltage cable segment with a preset high-voltage cable segment fault risk estimation index reasonable threshold value; if the fault risk estimation index of a potential fault high-voltage cable segment is greater than or equal to the preset high-voltage cable segment fault risk estimation index reasonable threshold value, then the potential fault high-voltage cable segment is recorded as a warning fault high-voltage cable segment, and then the warning fault high-voltage cable segments are screened out.

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