A primary and secondary fusion integrated ring network box fault diagnosis method and system

Abstract

The application relates to the technical field of fault prediction and health management, in particular to a primary-secondary fusion integrated ring network box fault diagnosis method and system. The method comprises the following steps: collecting three-phase instantaneous voltage and current signals in real time and converting the signals into digitized transient data; performing time window preprocessing on the digitized transient data and executing wavelet packet decomposition to generate a transient characteristic vector; calculating and analyzing the transient characteristic vector through a transient zero sequence power direction method and a support vector machine model to generate a local diagnosis result; when the local diagnosis result is that cooperative positioning needs to be started, calculating transient current similarity coefficients and transient waveform intensity difference coefficients based on the digitized transient data to generate a comprehensive positioning result; determining a fault line according to the comprehensive positioning result and generating a remote control command; executing fault isolation operation based on the remote control command and executing a PHM process. Through deep fusion of double local transient diagnosis and cross-terminal cooperative positioning, the application realizes high-precision determination of a fault section boundary.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fault prediction and health management, in particular to a primary and secondary fusion integrated ring main unit fault diagnosis method and system. BACKGROUND

[0002] In the field of fault prediction and health management of ring main units, the existing technology mainly adopts centralized architecture for fault prediction and health management (PHM). Under this architecture, the main responsibility of the distribution terminal unit (DTU) configured inside the ring main unit is data acquisition and uploading. The terminal device only reports electrical information such as current and voltage to the master station system located in the substation or control center. The master station system is responsible for centralized data analysis, fault judgment, decision making, and issuing remote control commands to the terminal device to achieve fault isolation and recovery.

[0003] However, the existing fault line selection technology is fundamentally limited by the topology structure. Ring main units are applied to medium voltage distribution networks and belong to open-loop systems in electrical wiring. In widely used small current grounding systems (such as neutral point ungrounded or grounded through arc suppression coil), the traditional fault line selection principle (such as the principle based on steady-state zero sequence current) is designed for closed-loop systems such as main substations. Due to the open-loop topology structure of the ring main unit, the sum of the zero sequence currents of all outgoing lines is not zero, which makes any traditional method that only monitors the relationship between zero sequence currents or is based on steady-state quantities will draw incorrect diagnostic results in the scenarios of busbar fault, upstream fault or downstream fault of outgoing lines, forming a line selection blind area. Therefore, under the superimposed limitation of the existing centralized architecture and the open-loop topology of the ring main unit, the system cannot accurately select lines and independently isolate faults in the highest proportion of small current grounding faults.

[0004] Therefore, a primary and secondary fusion integrated ring main unit fault diagnosis method and system is proposed. SUMMARY

[0005] The purpose of the present application is to provide a primary and secondary fusion integrated ring main unit fault diagnosis method and system for fault diagnosis of ring main units.

[0006] To achieve the above purpose, the present application provides the following technical solutions:

[0007] A primary and secondary fusion integrated ring main unit fault diagnosis method and system, comprising

[0008] Real-time synchronous acquisition of three-phase instantaneous voltage and instantaneous current signals of each feeder port, and conversion into digitized transient data;

[0009] Based on the time of fault occurrence, the digitized transient data is preprocessed by time window, and zero sequence waveform data is extracted; wavelet packet decomposition is performed on the zero sequence waveform data to generate a transient feature vector;

[0010] The polarity result is generated by component extraction and integral calculation of the zero sequence waveform data through the transient zero sequence power direction method; the directivity index is output by regression analysis and weighted summation of the transient feature vector through the pre-trained support vector machine model; the local diagnosis result is generated based on the polarity result and the directivity index;

[0011] When the local diagnosis result is to start cooperative positioning, the ring network box requests exchange of digitized transient data from the adjacent ring network box terminal through the communication network; the transient current similarity coefficient and the transient waveform intensity difference coefficient are calculated based on the digitized transient data of the adjacent terminal, and the comprehensive positioning result is generated in combination with the local diagnosis result;

[0012] The fault line is determined according to the comprehensive positioning result, and a remote control command is generated; the fault isolation operation is performed based on the remote control command, and the PHM process is performed.

[0013] Preferably, the specific generation process of the digitized transient data is: real-time acquisition of three-phase instantaneous voltage and current signals through the primary equipment sensor integrated by the ring network box; in the acquisition process, the three-phase instantaneous voltage and current signals are synchronized by a clock source at the hardware level, and the three-phase instantaneous voltage and current signals are digitized by an analog-to-digital converter to generate digitized transient data; the digitized transient data is stored in RAM, and the digitized transient data is locked and extracted through a fault transient triggering mechanism; the fault transient triggering mechanism is based on detection of line current, and when the absolute change rate of zero sequence current and / or zero sequence voltage of any feeder port exceeds the threshold value, the fault transient triggering mechanism is triggered.

[0014] Preferably, the specific generation method of the transient feature vector includes: selecting a preset time window located before and after the fault occurrence time through the positioning fault occurrence time; in the preset time window, superimposed calculation is performed on the three-phase instantaneous voltage and current to extract zero sequence waveform data containing instantaneous zero sequence voltage and zero sequence current; multi-layer wavelet packet decomposition is performed on the zero sequence waveform data, the multi-layer wavelet packet decomposition uses a mother wavelet base, and the number of decomposition layers is set to divide the entire frequency band of the zero sequence waveform data into a plurality of non-overlapping sub-bands; in the offline stage, a power distribution network simulation model is constructed using electromagnetic transient simulation software, different working conditions of fault mechanism are simulated through the power distribution network simulation model, and electromagnetic transient simulation results are generated; according to the electromagnetic transient simulation results, transient energy analysis is performed on each sub-band, and the sub-bands are selected based on the transient energy concentration degree and the transient energy ratio; the wavelet packet energy value and the cross-correlation coefficient of each selected sub-band are calculated, and all selected sub-bands are arranged in frequency increasing order, and the finally generated transient feature vector is composed of three parts: current energy sequence, voltage energy sequence and voltage current cross-correlation coefficient sequence arranged in frequency increasing order.

[0015] Preferably, the generating process of the local diagnosis result comprises: generating a polarity result by component extraction and integral calculation of the zero sequence waveform data through a transient zero sequence power direction method; the specific process of the transient zero sequence power direction method is: extracting transient zero sequence components by digital filtering and differential processing of the zero sequence voltage and the zero sequence current of the zero sequence waveform data; the digital filtering and differential processing is realized through a digital differential filter; calculating transient zero sequence instantaneous power integral values of the transient zero sequence components by an instantaneous power algorithm, and judging the polarity result; outputting a multi-frequency admittance feature vector with equal dimensions and a selected number of frequency bands by regression analysis of transient feature vectors through a support vector machine model; the support vector machine model adopts a radial basis function as a kernel function, and is trained based on different transient simulation data; each component of the multi-frequency admittance feature vector is a complex ratio of a transient current signal to a transient voltage signal in a corresponding frequency band; generating a directivity index by weighted summation of each component of the multi-frequency admittance feature vector; fusing the polarity result and the directivity index by logical AND to generate the local diagnosis result, wherein the local diagnosis result contains a direction indication and a result type; when the directivity index and the polarity result both indicate the same direction, the result type of the local diagnosis result is local isolation; only when one of the following conditions is met: the fault directions represented by the polarity result and the directivity index are inconsistent, the reliability of the polarity result is lower than a preset reliability threshold, and the reliability of the directivity index is lower than the preset reliability threshold, the result type of the local diagnosis result is cooperative positioning.

[0016] Preferably, the specific process of the exchanging digitized transient data is: when the local diagnosis result is determined to be cooperative positioning, sending a request instruction of exchanging digitized transient data to a directly connected adjacent ring network box terminal through a communication network inside the power distribution network; the request instruction requires that the digitized transient data returned by the adjacent terminal is within the same time window of the fault occurrence time; the digitized transient data is losslessly encoded through differential encoding.

[0017] Preferably, the generation process of the comprehensive positioning result is as follows: after the ring network box receives the synchronous zero sequence current waveform data of the adjacent terminal, the Pearson correlation coefficient between the zero sequence current waveform of the terminal and the zero sequence current waveform of the adjacent terminal is calculated as a transient current similarity coefficient; at the same time, the transient waveform intensity difference coefficient between the waveforms of the terminal and the adjacent terminal is calculated, the transient waveform intensity difference coefficient being the absolute value of the difference between the transient waveform intensity indexes of the waveforms of the terminal and the adjacent terminal, and the transient waveform intensity index being the integral of the square of the zero sequence current waveform; the calculated transient current similarity coefficient and transient waveform intensity difference coefficient are logically judged with the local diagnosis result; if the transient current similarity coefficient is greater than a preset similarity threshold and the transient waveform intensity difference coefficient is less than a preset energy difference threshold, it is determined that there is no fault section boundary between the two terminals; if the transient current similarity coefficient is less than the preset similarity threshold and the transient waveform intensity difference coefficient is greater than the preset energy difference threshold, it is determined that there is a first type of candidate fault section boundary between the two terminals; all the remaining sections not belonging to the above logical judgment are determined as second type of candidate fault section boundary; the ring network box determines the fault section boundary by comparing the transient current similarity coefficients and transient waveform intensity difference coefficients of all adjacent sections and combining the direction indication of the local diagnosis result; the process of determining the fault section boundary is as follows: excluding the sections determined as not having fault section boundaries; taking the first type of candidate fault section boundary and the second type of candidate fault section boundary as candidate boundaries, and selecting the candidate boundary consistent with the direction indication of the local diagnosis result as the fault section boundary; generating a fault section identifier based on the fault section boundary, and the fault section identifier is the comprehensive positioning result.

[0018] Preferably, the specific process of executing the fault isolation operation and the PHM process based on the remote control command is as follows: according to the comprehensive positioning result, the section located is mapped to a physical fault line by querying the distribution network topology and the device connection table of the ring network box; the ring network box generates a remote control command according to the built-in fault handling strategy model; under the premise that the fault current has been cleared, the generated remote control command is directly sent to the intelligent operating mechanism of the circuit breaker integrated in the ring network box through the integrated digital interface, and the PHM process is started after the operation is completed, wherein the PHM process is as follows: the ring network box records the cumulative operation number, fault current level and operation time stamp of the device, and generates fault operation data; a device health degradation model is constructed based on the cumulative operation number and current stress, and the mechanical life and electrical life consumption of the device are evaluated based on the fault operation data through the device health degradation model, and the device health status index and remaining service life are updated.

[0019] A primary and secondary fusion complete ring network box fault diagnosis system, comprising:

[0020] A collection and perception module is configured to synchronously collect three-phase instantaneous voltage and instantaneous current signals of each feeder port in real time and convert the signals into digitized transient data;

[0021] A data processing and synchronization module is configured to perform time window preprocessing on the digitized transient data based on a fault occurrence time, extract zero sequence waveform data, perform wavelet packet decomposition on the zero sequence waveform data, and generate a transient feature vector;

[0022] A local diagnosis decision module is configured to perform component extraction and integral calculation on the zero sequence waveform data by a transient zero sequence power direction method, generate a polarity result, perform regression analysis and weighted summation on the transient feature vector by a pre-trained support vector machine model, output a directivity index, and generate a local diagnosis result based on the polarity result and the directivity index;

[0023] A cooperative positioning and control execution module is configured to request neighboring ring network cabinet terminals to exchange digitized transient data through a communication network when the local diagnosis result indicates that cooperative positioning needs to be started, calculate a transient current similarity coefficient and a transient waveform intensity difference coefficient based on the digitized transient data of the neighboring terminals, generate a comprehensive positioning result in combination with the local diagnosis result, determine a fault line based on the comprehensive positioning result, generate a remote control command, perform fault isolation operation based on the remote control command, and perform a PHM process.

[0024] Compared with the prior art, the present application has the following advantages:

[0025] 1. When the local diagnosis is uncertain, the present application can accurately determine the fault section boundary based on the calculation of the transient current similarity coefficient and the transient waveform intensity difference coefficient in combination with the direction indication of the local diagnosis result, overcoming the limitation of open-loop topology, avoiding the situation that the ring network cabinet derives incorrect diagnosis results in the bus fault, upstream fault or downstream fault of the outgoing line, forming a line selection blind area, and realizing accurate line selection and local autonomous isolation of the highest proportion of small current grounding faults.

[0026] 2. The present application proposes a local diagnosis combining the transient zero sequence power direction method and the multi-frequency admittance method, and introduces a cooperative positioning mechanism, which can uniquely and accurately determine the section boundary where the fault current waveform changes dramatically, overcoming the limitation of the prior art that only relies on the steady-state zero sequence current relationship and is easy to misjudge, and greatly improving the diagnosis accuracy of the fault detection method for complex small current grounding faults.

[0027] 3、The application extracts the zero sequence current waveform in the preset time window of the fault occurrence time and performs multi-layer wavelet packet decomposition to generate a transient feature vector of a selected frequency band containing fault characteristics; the fault diagnosis model can capture the weak and high frequency characteristics of the small current grounding fault, thereby greatly improving the fault detection sensitivity and anti-interference ability of the system in the small current grounding system. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 A flowchart of the primary and secondary fusion complete ring net box fault diagnosis method of the application;

[0029] Figure 2 A structural schematic diagram of the primary and secondary fusion complete ring net box fault diagnosis system of the application;

[0030] Figure 3 A flowchart of generating a local diagnosis result of the application;

[0031] Figure 4 A flowchart of generating a comprehensive positioning result of the application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0033] Please refer to Figures 1 to 4 The application provides a primary and secondary fusion complete ring net box fault diagnosis method and system, and the technical solutions are as follows:

[0034] Embodiment one:

[0035] Real-time synchronous acquisition of three-phase instantaneous voltage and instantaneous current signals of each feeder port is performed, and the signals are converted into digitized transient data;

[0036] Time window preprocessing of the digitized transient data is performed based on the fault occurrence time, and zero sequence waveform data is extracted; wavelet packet decomposition is performed on the zero sequence waveform data to generate a transient feature vector;

[0037] Component extraction and integral calculation of the zero sequence waveform data are performed through the transient zero sequence power direction method to generate a polarity result; regression analysis and weighted summation of the transient feature vector are performed through a pre-trained support vector machine model to output a directivity index; a local diagnosis result is generated based on the polarity result and the directivity index;

[0038] When the local diagnosis result is that cooperative positioning needs to be started, the ring main unit requests neighboring ring main unit terminals to exchange digitized transient data through a communication network; transient current similarity coefficients and transient waveform intensity difference coefficients are calculated based on the digitized transient data of the neighboring terminals, and a comprehensive positioning result is generated in combination with the local diagnosis result;

[0039] A fault line is determined according to the comprehensive positioning result, and a remote control command is generated; a fault isolation operation is performed based on the remote control command, and a PHM process is performed.

[0040] Further, the specific generation process of the digitized transient data is as follows: three-phase instantaneous voltage and current signals are collected in real time through a primary equipment sensor integrated by the ring main unit; in the collection process, the three-phase instantaneous voltage and current signals are synchronized by a clock source at a hardware level, and are digitized by an analog-to-digital converter to generate digitized transient data; the digitized transient data are stored in a RAM, and are locked and extracted by a fault transient triggering mechanism; the fault transient triggering mechanism is triggered when the absolute change rate of zero sequence current and / or zero sequence voltage of any feeder port exceeds a threshold based on detection of line current.

[0041] Specifically, in the embodiment, the primary equipment sensor adopts an electronic transformer based on a Rogowski coil and a voltage divider, the frequency response bandwidth of the electronic transformer needs to reach 20 kHz or more, and the measurement accuracy level should reach 0.2S level, so as to ensure accurate collection of high-frequency transient signals. The sampling rate of the ADC is 80 kHz, and the bit depth is preferably 16 bits or more, so as to ensure accurate capture and digitization of weak transient signals. The high-precision clock source adopts a GPS / Beidou timing PTP master clock, and the synchronization accuracy is less than or equal to 1 microsecond. The trigger logic of the fault transient triggering mechanism is set to OR logic, that is, it is triggered when any of the following conditions is met: the absolute change rate of the zero sequence voltage of any feeder port exceeds the minimum trigger level for distinguishing normal operating conditions from minimum fault transients; the absolute change rate of the zero sequence current exceeds the minimum trigger level for distinguishing normal operating conditions from minimum fault transients. The minimum trigger level must be higher than the absolute change rate of the maximum power frequency zero sequence component that may occur in the normal operating state and lower than the maximum absolute change rate of the transient traveling wave generated by the minimum expected fault. The fault transient triggering mechanism adopts an independent high-speed logic circuit for real-time calculation. After the mechanism is triggered, the system locks and extracts digitized transient data containing a preset time length before and after the fault occurs, the preset time length completely contains the whole process waveform information before and after the fault occurs, and the range is relatively long, which is set to 5 ms before the fault and 50 ms after the fault.

[0042] The application can effectively avoid the calculation error of transient waveform correlation caused by terminal clock deviation by configuring an integrated sensor and adopting hardware-level timestamp synchronization and high-precision analog-digital conversion, and ensures the accuracy of the overall diagnosis method.

[0043] Further, the specific generation manner of the transient feature vector comprises: positioning a fault occurrence time, selecting a preset time window located before and after the fault occurrence time; superimposing calculation of three-phase instantaneous voltage and current in the preset time window, extracting zero sequence waveform data containing instantaneous zero sequence voltage and zero sequence current; performing multi-layer wavelet packet decomposition on the zero sequence waveform data, the multi-layer wavelet packet decomposition adopts a mother wavelet base and sets a decomposition layer number, and the entire frequency band of the zero sequence waveform data is divided into a plurality of non-overlapping sub-frequency bands; in an offline stage, an electromagnetic transient simulation software is used to construct a power distribution network simulation model, a fault mechanism under different working conditions is simulated through the power distribution network simulation model, and an electromagnetic transient simulation result is generated; according to the electromagnetic transient simulation result, transient energy analysis is performed on each sub-frequency band, and the sub-frequency band is selected based on transient energy concentration degree and transient energy ratio; the wavelet packet energy value and the cross-correlation coefficient of each selected sub-frequency band are calculated, and all selected sub-frequency bands are arranged in frequency increasing order, and the finally generated transient feature vector is composed of three parts: the current energy sequence, the voltage energy sequence and the voltage-current cross-correlation coefficient sequence arranged in frequency increasing order.

[0044] Specifically, in the embodiment, the preset time window is set to a duration that must be less than the round-trip propagation time of the fault traveling wave from the ring net box feeder port to the nearest electrical discontinuity point (for example, a busbar or a transformer). The selection of the duration strictly follows the principle of distinguishing the first traveling wave, and ensures that the extracted transient feature vector only contains the propagation information of the first traveling wave; the starting time of the time window is set to a very short time interval after the fault transient triggering time, so as to eliminate the glitch interference caused by high-frequency digital differentiation at the triggering moment. The calculation of the zero sequence waveform data includes the calculation of instantaneous zero sequence current and the calculation of instantaneous zero sequence voltage The calculation of the instantaneous zero sequence current is 1 / 3 of the arithmetic sum of three-phase instantaneous current ; similarly, the calculation of the instantaneous zero sequence voltage is 1 / 3 of the arithmetic sum of three-phase instantaneous voltage;

[0045] The mother wavelet base used in the multi-layer wavelet packet decomposition is specifically db4, and the number of decomposition layers is specifically 4, so as to divide the entire frequency band of the signal into 16 non-overlapping sub-bands; the selected frequency bands are specifically 5, and the selected frequency bands are the first 7 frequency bands with the highest transient energy concentration in the 16 sub-bands. And the first 8 frequency bands with the highest transient energy ratio in the 16 sub-bands. The final selected 5 frequency bands are the intersection of the two groups of frequency bands that meet the highest standard. The specific division of the 5 frequency bands is according to the 4-layer db4 wavelet packet decomposition result, and the theoretical bandwidth of each sub-band is 2.5 kHz. The specific frequency band and frequency interval (taking a sampling rate of 80 kHz as an example) are shown in Table 1:

[0046] Table 1 Frequency band frequency interval table

[0047]

[0048] The dimension of the finally formed transient feature vector is consistent with the number of selected frequency bands, which is 5 dimensions.

[0049] The process of the electromagnetic transient simulation result specifically includes: using an electromagnetic transient simulation software (PSCAD / EMTDC) to construct a distribution network simulation model, simulating the fault mechanism of different working conditions and fault types (especially small current grounding faults) on the simulation model. Run the simulation and obtain the voltage and current transient waveform data measured by the ring net box at the time of fault occurrence. Perform wavelet packet decomposition on the transient data obtained by simulation to obtain the wavelet packet energy of different sub-bands, so as to determine which frequency bands have the most prominent fault characteristics. The distribution network simulation model constructed by the electromagnetic transient simulation software uses a multi-phase, frequency-variable parameter line model to accurately simulate the propagation and attenuation characteristics of transient traveling waves at high frequencies. The grounding mode of the distribution network system in the simulation model is a small current grounding system, and a constant impedance load model is used. The sampling rate of the simulation run should be consistent with the sampling rate of the actual collection system (preferably 80 kHz or higher).

[0050] The transient energy concentration is the proportion of the sub-band wavelet packet energy to the total energy, and the specific generation process of the transient energy ratio is: collecting data under normal operating conditions (no fault) and calculating the wavelet packet energy of the sub-band to generate normal operating condition energy, collecting data under fault conditions and calculating the wavelet packet energy of the sub-band to generate fault operating condition energy. The transient energy ratio is the ratio of the fault operating condition energy to the normal operating condition energy.

[0051] The specific process of calculating the wavelet packet energy value and the cross-correlation coefficient of each selected sub-band is as follows: calculating the square sum of the zero sequence current decomposition coefficient in the frequency band to obtain the current frequency band energy; calculating the square sum of the zero sequence voltage decomposition coefficient in the frequency band to obtain the voltage frequency band energy; and calculating the cross-correlation coefficient of the zero sequence voltage decomposition coefficient and the zero sequence current decomposition coefficient in the frequency band. The cross-correlation coefficient is obtained by multiplying the corresponding voltage coefficient and current coefficient, summing them up, and then dividing by the square root of the product of the voltage energy and the current energy. The coefficient reflects the similarity and polarity relationship of the voltage waveform and the current waveform in the time domain, thereby implicitly reflecting the phase characteristics of the fault.

[0052] The finally generated transient feature vector is composed of three parts, i.e., a current frequency band energy sequence, a voltage frequency band energy sequence, and a cross-correlation coefficient sequence arranged in ascending order of frequency. The combined feature vector can represent the energy size of the fault and the relative phase relationship between the voltage and the current.

[0053] The present application realizes the joint analysis of the transient signal in the time domain and the frequency domain by performing multi-layer wavelet packet decomposition on the zero sequence waveform data, effectively separates the fault characteristics from the background noise and the power frequency interference, and avoids blind selection, thereby significantly improving the discriminability and sensitivity of the feature vector.

[0054] Further, the generation process of the local diagnosis result includes: generating a polarity result by performing component extraction and integral calculation on the zero sequence waveform data through a transient zero sequence power direction method; the specific process of the transient zero sequence power direction method is as follows: performing digital filtering and differential processing on the zero sequence voltage and the zero sequence current of the zero sequence waveform data to extract a transient zero sequence component; the digital filtering and differential processing is realized through a digital differential filter; performing transient zero sequence instantaneous power integral value calculation on the transient zero sequence component by using an instantaneous power algorithm, and judging the polarity result; performing regression analysis on the transient feature vector by using a support vector machine model to output a multi-frequency admittance feature vector with the same number of components as the selected frequency bands; the support vector machine model uses a radial basis function as a kernel function, and the support vector machine model is trained based on different transient simulation data; each component of the multi-frequency admittance feature vector is a complex ratio of the transient current signal and the transient voltage signal in the corresponding frequency band; performing weighted sum on each component of the multi-frequency admittance feature vector to generate a directivity index; performing logical and fusion on the polarity result and the directivity index to generate a local diagnosis result, wherein the local diagnosis result includes a direction indication and a result type; when the directivity index and the polarity result both indicate the same direction, the result type of the local diagnosis result is local isolation; the result type of the local diagnosis result is cooperative positioning only when one of the following conditions is met: the fault directions represented by the polarity result and the directivity index are inconsistent, the reliability of the polarity result is lower than a preset reliability threshold, and the reliability of the directivity index is lower than the preset reliability threshold.

[0055] Specifically, the digital differential filter adopts a FIR (Finite Impulse Response) structure, and the filter order is N order (N is preferably 10), so as to realize approximate linear phase shift and minimum delay, and ensure that the extraction of the transient zero sequence component does not interfere with the waveform polarity. The difference equation of the filter is: Wherein is the sampled value of the input zero sequence waveform, is the filtered transient zero sequence component, is the coefficient of the differential filter, which is obtained by least square optimization, represents the index of the discrete time sequence, indicating that the data of the current processing is the data of the sampling point, represents the order index of the filter, which is used to indicate the delay amount of the input sequence. The coefficient design of the filter should be on the premise of ensuring that the group delay is less than 50 microseconds, while the power frequency and its low harmonic components are suppressed to the maximum extent, and the high frequency band with concentrated transient traveling wave energy is accurately linearly phase-shifted and differentiated. The order design of the differentiator must be fitted with high precision (for example, using Lagrange interpolation method), so as to ensure that the amplitude error in the target transient frequency range (for example, 3 kHz to 15 kHz) is less than 0.5%, so as to effectively suppress the negative influence of power frequency components and acquisition noise on direction judgment while amplifying the useful transient signal.

[0056] The instantaneous power algorithm is used to calculate the transient zero sequence instantaneous power The value of the transient zero sequence instantaneous power is equal to the product of the transient zero sequence voltage and the transient zero sequence current obtained after digital filtering and differentiation. The calculation of the transient zero sequence instantaneous power integral value is based on the calculation of the above-mentioned instantaneous power , The calculation of the transient zero sequence instantaneous power integral value is the cumulative summation (integration) of the instantaneous power in a specific time interval. The integration interval starts from the fault occurrence time and lasts for the fault occurrence time plus the integration duration . Wherein, the integration duration should be determined according to the shortest section length of the adjacent line of the ring box in the distribution network; the integration duration must be strictly shorter than the round-trip propagation time of the fault traveling wave from the measurement point to the nearest reflection point (the opposite side of the shortest adjacent line section), so as to ensure that only the first wave information is included in the integration time, thereby effectively excluding the interference of reflected waves on power direction judgment.

[0057] The specific process of determining the polarity result is: before determining the polarity, the system first performs validity check: calculating the maximum instantaneous value of the transient zero sequence current in the preset time window of the fault occurrence time; only when the maximum instantaneous value exceeds the fault current amplitude threshold, the subsequent polarity determination is performed, the fault current amplitude threshold should be at least 10% higher than the maximum instantaneous value of the normal system unbalanced current and background noise; otherwise, if the validity check fails, the polarity result is not generated. Since the local diagnosis result lacks direction indication information at this time, the reliability of the polarity result is determined to be lower than the preset reliability threshold, the result type of the local diagnosis result is determined to be to start cooperative positioning, and the direction indication is empty or keeps the state of the previous time. For the data that passes the check, set the direction from the ring net box bus side to the feeder side as the positive reference direction, if the calculated polarity result is negative, it represents that the power flows to the bus, then it is judged that the fault is in the ring net box bus or the upstream power supply side thereof; if the polarity result is positive, it represents that the power flows to the line, then it is judged that the fault is in the feeder side.

[0058] The support vector machine model constructs two independent regression sub-models for each selected frequency band: one is used to predict the modulus of the frequency band admittance, and the other is used to predict the phase angle of the frequency band admittance. Although the input transient feature vector only contains energy coefficients, due to the nonlinear inherent mapping relationship between the energy distribution of the transient traveling wave and the fault point distance and the path impedance (complex number), through the training of a large amount of full-phase simulation data, the model can implicitly learn this mapping, and thus the modulus and phase angle are respectively regressed.

[0059] The support vector machine model adopts radial basis function (RBF) as the kernel function, and the form of the RBF kernel function is: wherein, and is the input transient feature vector, is an important parameter of the kernel function, which controls the distribution range of the data in the high-dimensional space. The training of the model is based on a large amount of transient simulation data of different fault types and fault positions. The training data must cover: different fault types (such as single-phase grounding, two-phase grounding, phase-to-phase short circuit, etc.), different fault distances (from the ring net box bus to the end of the line), different transient operating conditions (such as different loads, different grounding resistances), and the labels are generated: the output label (multi-frequency admittance feature vector) corresponding to each set of simulation data (input transient feature vector) is calculated in advance according to the actual physical parameters of the simulation model and the fault position. In the model training process, the two key hyperparameters and the kernel function parameter must be optimized by cross-validation method.

[0060] The components of the multi-frequency admittance feature vector are generated by calculating the complex ratio of the transient current signal to the transient voltage signal in each selected frequency band. Specifically, the complex ratio is obtained by performing short-time Fourier transform (STFT) on the zero-sequence waveform data, extracting the phasors of the current and voltage in the corresponding frequency band, and calculating the phasor ratio. In this way, a multi-frequency admittance feature vector with dimensions equal to the number of selected frequency bands is generated. To ensure the integrity of the electrical physical information, each component of the multi-frequency transient admittance feature vector must contain both the modulus and the phase angle information of the admittance. Specifically, each component of the feature vector is composed of its modulus and phase angle. The modulus is the ratio of the envelope amplitude of the transient current signal to the envelope amplitude of the transient voltage signal in the corresponding frequency band; the phase angle is the phase difference between the transient current signal and the transient voltage signal in the corresponding frequency band.

[0061] For the training of the support vector machine model, the output label (i.e. the real multi-frequency admittance feature vector) is generated by calculating the inverse of the theoretical equivalent impedance from the fault point to the measurement point at the center frequency of the frequency band. The modulus and phase angle of the complex admittance are taken as the two components of the standard output label of the training sample. Since the admittance feature vector is a vector with 2K real components (where K is the number of frequency bands), the support vector machine model is configured as a multi-output regression model, which aims to simultaneously regress the modulus and phase angle of each frequency band. In this way, high-precision directional regression analysis of fault distance and direction is achieved.

[0062] The directional index is generated by weighted summing the components of the multi-frequency admittance feature vector, which consists of five components, each representing the comprehensive feature of the equivalent transient admittance in a selected frequency band. The five admittance feature components are multiplied by their respective weight coefficients , respectively, and then all the product results are accumulated to obtain the final directional index, the weight coefficients are set for each frequency band, and their values are determined based on electromagnetic transient simulation results and fault sensitivity analysis. The sum of all weight coefficients should be equal to 1.

[0063] The weight coefficients The establishment process is specifically: based on electromagnetic transient simulation data, the Pearson correlation coefficient between the transient energy change amount and the fault distance change amount of each selected frequency band is calculated; the absolute value of the Pearson correlation coefficient is taken as the sensitivity factor of the frequency band; the weight is normalized, and the specific normalization process is: the sensitivity factor values of all selected selected frequency bands are counted; the arithmetic sum of the sensitivity factor values is calculated; the sensitivity factor value of each frequency band is divided by the arithmetic sum, and the quotient is the weight coefficient corresponding to the frequency band. The calculation logic ensures that the sum of all frequency band weight coefficients is strictly equal to 1, so that the frequency band with higher sensitivity occupies a larger proportion in the final diagnosis result.

[0064] The calculation of the polarity result reliability is based on the integral value of the transient zero sequence instantaneous power The reliability is defined as: comparing the absolute value of the integral value of the instantaneous power with the equivalent noise energy level estimated by the system background noise, signal acquisition error and other factors to obtain a ratio. The larger the ratio, the stronger the energy of the transient traveling wave signal, the better the ability to drown out noise, and the higher the reliability of direction judgment. The directivity index reliability is obtained according to the prediction residual statistical value or cross-validation error accumulated by the model during the training process. Specifically, the reliability is inversely proportional to the average prediction error of the model under different fault scenarios. The higher the reliability value, the closer the output prediction of the model to the current transient feature vector to the true physical label of the training data, and the higher the reliability of the directivity judgment. The reliability threshold values of the polarity result and the directivity index are empirical parameters determined by analyzing and counting a large amount of power distribution network electromagnetic transient simulation and field test data. The setting principle of these threshold values is: when the reliability of the polarity result is higher than the set threshold value, and the reliability of the directivity index is higher than the set threshold value, the correctness of the local diagnosis result can meet the established engineering requirements.

[0065] As an enhancement scheme of the support vector machine model, an online adaptive correction mechanism is introduced to fine-tune the key parameters of the SVM model using real-time collected confirmed non-fault event data (such as normal switching operation, lightning arrester action). The specific implementation is:

[0066] When the system detects a non-fault high-energy transient event (for example, the zero sequence current rate of change exceeds the threshold value but there is no subsequent isolation operation or the transient polarity result is determined to be a non-fault direction), the transient feature vector of the event is taken as the input, and the theoretical line impedance admittance value under normal operating state calculated in real time according to the power grid topology is taken as the standard output label, to construct a correction training set The goal of the correction mechanism is to fine-tune the weight coefficients and the kernel function parameters of the SVM model to minimize the correction training set The sum of squares of the previous regression errors. With an incremental learning algorithm, such as incremental support vector regression (ISVR) or a small batch online learning method based on gradient descent, the time-consuming global model retraining is avoided for each correction. The algorithm only slightly adjusts the current support vector set and kernel function parameters based on the data The correction process is completed within 50 milliseconds, and does not cause significant delay to the main diagnostic process. Correction frequency limit: To ensure model stability, set the minimum time interval of the correction mechanism (e.g. maximum trigger once every 24 hours), to prevent frequent model drift due to abnormal data collection.

[0067] By introducing an online adaptive correction mechanism, the main problem of applying a static model in a dynamic power grid environment is solved, significantly improving the long-term reliability and continuous accuracy of local diagnosis.

[0068] The application combines two complementary transient analysis techniques for local diagnosis, greatly reducing the risk of misjudgment by a single method, ensuring high reliability of the ring main unit when performing autonomous isolation operations.

[0069] Further, the specific process of exchanging digitalized transient data is as follows: when the local diagnosis result is determined to start cooperative positioning, send a request instruction to exchange digitalized transient data to the adjacent ring main unit terminal directly connected through the communication network inside the distribution network; the request instruction requires the digitalized transient data returned by the adjacent terminal to be within the same time window of the fault occurrence time; the digitalized transient data is losslessly encoded by differential encoding.

[0070] Specifically, the communication network is based on IEC 61850 GOOSE message; the digitalized transient data is losslessly encoded by differential encoding to minimize data transmission volume and reduce cooperative positioning communication delay. After receiving the instruction, the adjacent ring main unit terminal returns the differential encoded waveform record file (such as based on COMTRADE format) to the ring main unit through IEC 61850 MMS service.

[0071] The application exchanges data when cooperative positioning is started, ensuring efficient start and accurate calculation of the cooperative positioning mechanism. On-demand request (triggered only when local diagnosis is "need to start cooperative positioning") avoids a large amount of unnecessary communication load, optimizing the utilization rate of communication resources in the distribution network.

[0072] Further, the generation process of the comprehensive positioning result is: after the ring network box receives the synchronous zero sequence current waveform data of the adjacent terminal, the Pearson correlation coefficient between the zero sequence current waveform of the terminal and the zero sequence current waveform of the adjacent terminal is calculated as a transient current similarity coefficient; at the same time, the transient waveform intensity difference coefficient between the waveforms of the terminal and the adjacent terminal is calculated, the transient waveform intensity difference coefficient is the absolute value of the difference between the transient waveform intensity indexes of the waveforms of the terminal and the adjacent terminal, and the transient waveform intensity index is the integral of the square of the zero sequence current waveform; the calculated transient current similarity coefficient and transient waveform intensity difference coefficient are logically judged with the local diagnosis result; if the transient current similarity coefficient is greater than a preset similarity threshold, and the transient waveform intensity difference coefficient is less than a preset energy difference threshold, it is determined that there is no fault section boundary between the two terminals; if the transient current similarity coefficient is less than the preset similarity threshold, and the transient waveform intensity difference coefficient is greater than the preset energy difference threshold, it is determined that there is a first type of candidate fault section boundary between the two terminals; all the sections not belonging to the above logical judgment are determined as the second type of candidate fault section boundary; the ring network box determines the fault section boundary by comparing the transient current similarity coefficients and the transient waveform intensity difference coefficients of all adjacent sections, and combining the direction indication of the local diagnosis result; the determination process of the fault section boundary is: excluding the sections determined as not having the fault section boundary; taking the first type of candidate fault section boundary and the second type of candidate fault section boundary as candidate boundaries, and selecting the candidate boundary consistent with the direction indication of the local diagnosis result as the fault section boundary; generating a fault section identifier based on the fault section boundary, and the fault section identifier is the comprehensive positioning result.

[0073] Specifically, the calculation process of the Pearson correlation coefficient is: the average values of all sampling points in the zero sequence transient current waveform sequence collected by the ring network box and the adjacent ring network box are calculated respectively. For each sampling point in the sequence, the original value of the sampling point is subtracted from the average value of the sequence. The corresponding sampling point values after the centering processing are multiplied. Then, all the product results are accumulated and summed. The result of the accumulation and summation is divided by a standardization factor reflecting the fluctuation amplitude of the two waveforms, and the standardization factor is obtained by multiplying the fluctuation square sums of the two waveform sequences and taking the square root of the product result. The specific process of the fluctuation square sum is: the square of the difference between all sampling points and their average value is calculated, and all the square values are accumulated and summed. The finally calculated value is the transient current similarity coefficient.

[0074] The calculation of the transient waveform intensity index is the integral of the square of the zero sequence current waveform, and the integral time range should be the integral duration of the transient zero sequence instantaneous power integral value in the local diagnosis result. Consistency is ensured to capture only the energy of the initial fault traveling wave.

[0075] In the aforementioned logical judgment, the preset similarity threshold is set to 0.95 to ensure a high correlation between the waveforms; the preset energy difference threshold is set to 0.05 pu to ensure minimal transient energy difference between the two terminals. These thresholds are determined through statistical analysis and optimization of the electromagnetic transient simulation results of the distribution network simulation model. The specific process of the statistical analysis and optimization is as follows: Simulate two sample sets in the simulation model—intra-area faults and extra-area faults—and calculate the transient current similarity coefficient for each sample; plot the probability density curves of the coefficient distributions of the two types of samples, and select the value corresponding to the intersection of the two curves as the initial threshold; further, through receiver operating characteristic curve (ROC curve) analysis, select the value corresponding to the point that minimizes the sum of the false alarm rate and the missed alarm rate as the final preset similarity threshold.

[0076] The specific logic for determining the fault segment boundary is as follows: Segments deemed to lack a fault segment boundary are excluded; the first and second types of candidate fault segment boundaries are selected as candidate boundaries. Prioritize selecting the boundary from the first type of candidate fault segment boundaries that matches the direction indication of the local diagnostic results as the fault segment boundary; if there are no matching items in the first type of candidate boundaries or the first type of candidate boundaries is empty, then select the candidate boundary from the second type of candidate fault segment boundaries that matches the direction indication of the local diagnostic results as the fault segment boundary. If multiple candidate boundaries matching the direction indication exist, further compare the transient current similarity coefficients corresponding to these candidate boundaries, and select the segment with the smallest similarity coefficient as the fault segment boundary; if there is more than one segment with the smallest similarity coefficient, compare the corresponding transient waveform intensity difference coefficients, and select the segment with the largest energy difference coefficient as the unique fault segment boundary. This logic is based on the principle of lowest waveform correlation and largest energy difference within the fault segment.

[0077] As an enhancement to the comprehensive positioning results, a third cooperative positioning factor is introduced: the high-frequency energy ratio difference coefficient (FCRD). This coefficient is used to quantify the essential difference between fault points and non-fault points in high-frequency characteristic attenuation. The specific implementation method is as follows:

[0078] After performing wavelet packet decomposition to generate transient eigenvectors, the high-frequency band energy is calculated using the decomposition results. The high-frequency band energy Defined as the sum of squares of all wavelet packet coefficients in the transient eigenvector with frequencies ranging from 5 kHz to 12.5 kHz. Calculate the normalized high-frequency energy ratio. High-frequency energy is about to be generated. Divide by the sum of the squares of all wavelet packet coefficients in the transient eigenvector. Calculate the high-frequency energy ratio difference coefficient between this terminal and its neighboring terminals. . defined as the absolute difference of two terminal values. The logic judgment of integrating to the comprehensive positioning result is that the condition of no fault boundary in the section is enhanced as: the transient current similarity coefficient is greater than 0.95, and the transient waveform intensity difference coefficient is less than 0.05 p.u., and the high-frequency energy ratio difference coefficient is less than the preset threshold value of 0.02. The condition of determining the section as the first type of candidate fault section boundary is enhanced as: the transient current similarity coefficient is less than 0.95, and the transient waveform intensity difference coefficient is greater than 0.05 p.u., and the high-frequency energy ratio difference coefficient is greater than the preset threshold value of 0.10. When multiple second type of candidate fault section boundaries need to be finally distinguished, the largest section is selected as the final fault section boundary.

[0079] By introducing the high-frequency energy ratio difference coefficient (FCRD), a third orthogonal criterion is added on the basis of the existing waveform similarity and transient waveform intensity difference, thereby significantly improving the robustness and accuracy of the cooperative positioning.

[0080] By calculating the Pearson correlation coefficient (similarity) and the transient waveform intensity difference coefficient of the transient zero sequence current waveforms of adjacent terminals, quantitative and cross-terminal verification of the fault section boundary is realized. The uncertain local diagnosis result is converted into a unique and reliable comprehensive positioning result, which provides accurate coordinates for the final fault isolation.

[0081] Further, the specific process of executing the fault isolation operation and the PHM process based on the remote control command is: according to the comprehensive positioning result, the section located is mapped to the physical fault line by querying the distribution network topology and the equipment connection table of the ring network box; the ring network box generates a remote control command according to the built-in fault handling strategy model; under the premise that the fault current has been cleared, the generated remote control command is directly sent to the intelligent operating mechanism of the circuit breaker integrated in the ring network box through the integrated digital interface, and the PHM process is started after the operation is completed. The PHM process is: the ring network box records the cumulative operation number, fault current level and operation time stamp of the equipment, and generates fault operation data; a device health degradation model is constructed based on the cumulative operation number and current stress, and the mechanical life and electrical life consumption of the equipment are evaluated based on the fault operation data through the device health degradation model, and the device health status index and remaining service life are updated.

[0082] ​​​​The power distribution network topology and device connection table are stored in the form of an adjacency list, which records the logical section identifier of each feeder port of the ring network box, the connected physical line number, and the device ID and communication address of the associated circuit breaker, to realize accurate mapping from logical positioning results to physical device operating objects.

[0083] The fault processing strategy model is an expert system in the form of a rule base, and its input includes fault section identifier, fault type (such as small current ground fault), and current device operating state. The core decision rule of the model is: based on the upstream and downstream physical connection relationship of the fault section and the line protection coordination principle, a trip or opening remote control command is generated for the upstream circuit breaker and downstream load switch of the fault section, if the comprehensive positioning result indicates that the fault is located at the feeder side of the ring network box, an opening command is generated to isolate the feeder; if the fault section is located at the bus side of the ring network box or the upstream power supply side, a closing command or the existing state is maintained, and diagnostic information is reported to the master station.

[0084] Before generating the remote control command, the system first performs a safe opening capability check, and the specific process is as follows: querying the power distribution network device account, identifying whether the connected switch device type on the current fault line is 'circuit breaker' or 'load switch', and reading the rated short-circuit breaking current value of the device. The real-time monitored fault current amplitude is obtained, which is compared with the rated short-circuit breaking current of the device. If it is identified that the device is a circuit breaker, and the real-time fault current amplitude is less than its rated short-circuit breaking current, the system determines that it has safe opening capability, and generates a remote control command to immediately open, directly cutting off the fault line. If it is identified that the device is a load switch, or although it is a circuit breaker but the real-time fault current exceeds its rated breaking capacity, the system determines that it does not have direct opening capability. At this time, the system automatically locks the immediate opening function, and instead executes the no-voltage opening logic. That is: the system waits for the action of the upper substation protection device to trip, and when it is detected that the line voltage disappears and the current returns to zero, a closing command is generated to open the switch, and the isolation operation is completed before the upper power supply recloses.

[0085] The integrated digital interface is a special hardware circuit board for realizing digital communication between the distribution station terminal (DTU) and the primary equipment bay, which includes: a fiber transceiver (SFP / SFP+), a communication rate of 100 / 1000 Mbps, and no less than 2 optical ports; a master control chip (FPGA or high-performance DSP) that meets the real-time analysis and generation of SV messages (sample values) and GOOSE messages (control commands). A PTP slave clock chip with a synchronization accuracy of better than 1 microsecond, a buffer memory (RAM) with a cache capacity that meets the high-speed message cache requirement of at least 100 milliseconds, a power isolation and filtering circuit with an isolation voltage that meets the anti-interference level required by the IEC standard.

[0086] The circuit breaker intelligent operating mechanism is an integrated device integrating mechanical execution, control and monitoring functions. It contains: an operating executor, which is a permanent magnet operating mechanism or a high-energy electric spring mechanism, and the total opening and closing time is less than 30 milliseconds; an embedded microcontroller (single-chip microcomputer / MCU) adopting a dual-core heterogeneous architecture of "MCU+DSP" or "MCU+FPGA". Among them, the MCU has a main frequency of more than 300 MHz and is responsible for protocol stack and logic control; the DSP / FPGA acts as a coprocessor and is specially used for performing wavelet packet decomposition and parallel floating-point operation acceleration of SVM kernel functions to ensure that the processing time delay of the whole process of fault diagnosis is strictly controlled within 20 ms; a contact stroke displacement sensor with a detection accuracy of better than 0.1 millimeter; an electric parameter acquisition unit with a sampling frequency meeting the demand of fault current waveform monitoring; a non-volatile storage chip (such as Flash or FRAM) with a storage capacity meeting the demand of operation data storage for more than ten years; and a driving power switch circuit with rated current / voltage meeting the demand of instantaneous high-power driving of the operating mechanism coil or motor. In the embodiment, for the ring network box configured with a vacuum circuit breaker, the operating mechanism is configured to perform short-circuit current breaking operation; and for the ring network box configured with a sulfur hexafluoride load switch, the operating mechanism is configured to perform only opening operation when it is detected that the line has no current and no voltage, so as to cooperate with the above-mentioned no-voltage opening logic and ensure the safety of device operation.

[0087] The equipment health degradation model employs a contact wear calculation method based on weighted cumulative breaking current. The specific calculation logic is as follows: For each opening operation of the circuit breaker, the breaking current value is recorded, and this current value is exponentially calculated. The exponent value is typically set between 1.5 and 2.0 (for example, 1.9 to 2.0 for sulfur hexafluoride load switches and 1.5 to 1.7 for vacuum circuit breakers). The calculated value is multiplied by a preset wear coefficient to obtain the equivalent wear amount for a single operation. This wear coefficient is determined based on the ablation resistance test data of the contact alloy material, with a typical range of 0.0001 to 0.0005, thus quantifying the irreversible physical damage caused to the equipment by a single large current interruption. The system quantifies the electrical life consumption rate of the equipment by calculating the proportion of the cumulative equivalent wear amount to the maximum cumulative wear threshold, and further calculates the remaining service life percentage of the equipment. The maximum allowable cumulative wear threshold for the equipment is a reference value for the total equivalent wear amount set by the manufacturer based on the contact material, design thickness, and durability test results. For example, for a selected model of sulfur hexafluoride load switch, the maximum cumulative wear threshold is preferably set to 10,000 equivalent wear units. The equipment health status indicators include mechanical life attrition rate and electrical life attrition rate. The mechanical life attrition rate is the ratio of the equipment's cumulative number of operations to its designed mechanical life attrition rate. The electrical life attrition rate assesses the arc damage suffered by the contacts and arc-extinguishing chamber when interrupting fault current, based on the fault current level and its cumulative number of operations. The final determination of the equipment health status indicators and the equipment's remaining service life should be based on a conservative minimum value principle. That is, after calculating the mechanical life attrition rate and the electrical life attrition rate separately, their respective remaining life percentages are first calculated (i.e., 1 minus their respective attrition rates). Then, the final equipment remaining service life percentage is the lower of the mechanical remaining life percentage and the electrical remaining life percentage.

[0088] As an enhancement to the PHM process, PHM results are integrated with equipment stress models, spare parts inventory information, and the maintenance work order system to automatically generate optimized maintenance work orders with time windows. Specifically, this is achieved as follows:

[0089] Adding an operating stress factor to the PHM process The calculation, It is proportional to the square of the breaking current during circuit breaker operation, that is: in For fault current, For operation time, This is a material property constant. This factor is used to more accurately quantify the damage to the equipment contacts and arc-extinguishing chamber caused by each operation. Two maintenance trigger thresholds are set: a lifespan threshold and a maintenance trigger threshold. Triggered when the remaining useful life (RUL) of the circuit breaker is less than 60%. High stress accumulation threshold. : The cumulative operating stress factor of the equipment over three consecutive months The system triggers when the stress exceeds a preset 1.5 times the baseline stress. If either of the two aforementioned maintenance trigger thresholds is met, an electronic maintenance work order will be automatically created, detailing the equipment ID, the reason for triggering (insufficient RUL or excessive stress), and recommended maintenance items (e.g., contact inspection / replacement). The system then checks the spare parts inventory management system to confirm the availability of required spare parts (e.g., arc extinguishing chamber, operating mechanism springs); simultaneously, it checks the maintenance personnel scheduling system to match a suitable maintenance time window (e.g., planned power outage window). Based on the remaining percentage of RUL (lower RUL, higher priority) and the severity of the stress exceedance, the work order is assigned a high, medium, or low maintenance priority and pushed to the maintenance personnel's mobile terminal.

[0090] By transforming passive PHM assessment results into proactive maintenance actions and unplanned power outages into planned maintenance, a leap from condition monitoring to predictive maintenance has been achieved, resulting in significant operational benefits.

[0091] This invention ensures rapid and accurate fault isolation through isolation operations and a PHM (Prognostics and Health Management) process. It achieves a closed-loop fault handling system and intelligent operation and maintenance, effectively extending equipment lifespan and reducing maintenance costs.

[0092] This invention deeply integrates dual local transient diagnostics (power direction and multi-frequency admittance) with cross-terminal collaborative positioning, ensuring high-precision determination of fault segment boundaries. It overcomes the blind spots and uncertainties of traditional steady-state fault location methods in low-current grounding systems and open-loop topologies.

[0093] Example 2:

[0094] This application provides a primary and secondary integrated ring network box fault diagnosis system, referring to... Figure 2 This is a schematic diagram of a primary and secondary integrated ring network enclosure fault diagnosis system. The primary and secondary integrated ring network enclosure fault diagnosis system includes: an acquisition and sensing module, a data processing and synchronization module, a local diagnosis and decision module, and a collaborative positioning and control execution module.

[0095] Further, the acquisition and sensing module contains a high-frequency electronic transformer unit, a synchronous digitizing unit and a fault transient triggering and storage unit. The high-frequency electronic transformer unit is integrated based on Rogowski coil current transformer and voltage transformer technology based on voltage divider technology, which is used to real-time induction of three-phase transient voltage and current signals of each feeder port. The synchronous digitizing unit contains a high-precision GPS / Beidou timing PTP master clock source, a 16-bit high-precision analog-to-digital converter, which uses the clock source to stamp the collected signals with a hardware-level timestamp, converts the analog signals into digitized transient data, and ensures the timing accuracy of the stored waveforms. The fault transient triggering and storage unit is composed of a high-speed logic comparison circuit and a circular RAM memory, which is used to monitor the line state in real time and extract complete data from 5ms before fault to 50ms after fault from the RAM.

[0096] Further, the data processing and synchronization module contains a zero sequence waveform extraction unit, a multi-layer wavelet packet decomposition unit and a feature vector optimization selection unit. The zero sequence waveform extraction unit is composed of a digital signal processing chip, which is used to locate the fault occurrence time, intercept the preset time window data from 1ms to 5ms after the fault, and extract the instantaneous zero sequence voltage and current waveforms through superposition calculation. The multi-layer wavelet packet decomposition unit is an operation unit based on wavelet transform algorithm, which uses Daubechies4 (db4) mother wavelet basis to perform 4-layer wavelet packet decomposition on the zero sequence data, and divides the frequency band into 16 sub-bands. The feature vector optimization selection unit is composed of a distribution network simulation model interface, which is used to calculate the transient energy concentration and energy ratio of each sub-band in combination with the electromagnetic transient simulation results, automatically select 5 selected frequency bands reflecting the fault characteristics, and generate a 5-dimensional transient feature vector in ascending order of frequency.

[0097] Further, the local diagnostic decision module contains a transient polarity determination unit, a multi-frequency admittance regression analysis unit, and a decision logic fusion unit. The transient polarity determination unit is composed of a low-delay digital differential filter and an instantaneous power integrator, which is used to calculate and integrate the transient zero sequence instantaneous power. If the integration result is negative, it is determined to be a bus side fault; if it is positive, it is determined to be a feeder side fault. The multi-frequency admittance regression analysis unit is composed of a pre-trained support vector machine model, which uses a radial basis function as a kernel function, inputs the transient feature vector, and outputs a multi-frequency admittance feature vector. By weighted sum of each component, a directivity index is generated. The decision logic fusion unit is composed of a logic comparator, which is used to perform logical and fusion of the polarity result and the directivity index.

[0098] Further, the cooperative positioning and control execution module comprises a differential encoding communication unit, a comprehensive positioning calculation unit, a topology mapping and control unit, and a PHM intelligent operation and maintenance unit. The differential encoding communication unit is composed of an IEC61850 GOOSE-based communication interface. When a cooperative request is received, the transient data is differentially losslessly encoded and sent to the adjacent DTU. Meanwhile, the data returned by the adjacent terminal is received. The comprehensive positioning calculation unit is composed of a correlation analysis and difference coefficient calculation engine. It is used to calculate the transient current similarity coefficient and transient waveform intensity difference coefficient of the terminal and the adjacent terminal, and logically determine whether there is a fault section boundary between the two terminals. The topology mapping and control unit is composed of a topology storage and integrated digital interface, which is used to query the distribution network topology and map the determined fault section to the physical line. According to the fault handling strategy model, a remote control command is generated to directly drive the intelligent operating mechanism of the circuit breaker for isolation. The PHM intelligent operation and maintenance unit is composed of a life assessment model, which is used to update the remaining useful life (RUL) of the equipment, automatically trigger maintenance work orders and match spare parts inventory.

[0099] Embodiment three:

[0100] The embodiment of the present application takes the high resistance grounding fault of the underground cable due to aging insulation damage as a specific scenario. It focuses on the generation process of digital transient data, and describes in detail the specific implementation of front-end sensing and triggering to ensure the accuracy of source data.

[0101] An integrated primary equipment sensor is configured at each feeder port of the ring network box D. The sensor uses a current transformer based on Rogowski Coil and a voltage transformer technology of a voltage divider. The frequency response bandwidth of the sensor is set to be above 20 kHz, and the measurement accuracy level reaches 0.2S level, so as to ensure that the high-frequency transient signals at the fault instant are captured without distortion. In the signal acquisition process, a high-precision clock source (using GPS / Beidou timing PTP master clock) is introduced. The clock source stamps hardware-level time on the three-phase instantaneous voltage and current signals, and the synchronization accuracy is controlled within 1 microsecond, so as to eliminate the time deviation between multiple terminals. The analog signals are digitized by an analog-to-digital converter (ADC). The sampling rate of the ADC is set to be 80 kHz, and the bit depth is 16 bits. The generated digital transient data is stored in a loop RAM (random access memory) in real time for storage, waiting for a trigger instruction. The system runs an independent fault transient trigger mechanism, which monitors the line state in real time based on an independent high-speed logic circuit. The trigger logic is set to be or logic, that is, it is triggered when any one of the following conditions is met: the absolute rate of change of zero sequence voltage of any one feeder port exceeds 5000 kV / s; the absolute rate of change of zero sequence current exceeds 500 kA / s. Once triggered, the system immediately locks and extracts the data in the RAM, and the data segment range covers the complete waveform from 5 ms before the fault occurs to 50 ms after the fault.

[0102] Through the high-precision hardware-level synchronous acquisition of transient data, the time of fault occurrence and complete waveform data before and after the fault occurrence can be accurately captured, thereby providing high-quality original input for subsequent analysis.

[0103] Embodiment Four

[0104] The embodiment of the application refers to the specific scenario of Embodiment Three, and focuses on a local diagnosis method of transient power direction and multi-frequency admittance fusion. Refer to Figure 3 for a flowchart for generating a local diagnosis result.

[0105] The data processing and synchronization module of the ring box D has extracted accurate zero sequence voltage and current waveforms, and generated a 5-dimensional transient feature vector based on a selected high-frequency band. The transient polarity determination unit integrates the zero sequence power in a very short time window (such as 13.3 microseconds) after the fault occurs. Since the fault occurs at the downstream feeder side of D, the power integration result is positive (the power flows from the bus to the feeder), which preliminarily determines that it is a feeder side fault. The multi-frequency admittance regression analysis unit inputs the 5-dimensional feature vector into the SVM model. The SVM model combines the energy weights of each frequency band, and the output directivity index is significantly greater than zero, strongly pointing to the feeder side. The decision logic fusion unit performs logical AND judgment on the directivity index and the polarity result. Both are highly consistent and have high reliability. The system generates a "locally isolable" local diagnosis result in a very short time (for example, 20 ms), and immediately starts the tripping process.

[0106] Through the rapid fusion of double criteria, the ring box D accurately determines the fault direction in a very short time, avoids the expansion of the fault or unnecessary full-line tripping, and greatly improves the reliability and recovery speed of power supply.

[0107] Embodiment Five

[0108] The embodiment of the application refers to the specific scenario of Embodiment Three, and the local diagnosis result is "need to start cooperative positioning", which focuses on cooperative positioning of waveform similarity and energy difference. Refer to Figure 4 for a flowchart for generating a comprehensive positioning result.

[0109] The fault occurs on a branch cable of G-H section. After the local diagnosis of ring net box G, the directive index is ambiguous due to the similar distance between the bus side and the feeder side, and the decision is to start the cooperative positioning. Ring net box G immediately requests the synchronous and differentially encoded fault transient data from adjacent terminals F and H through GOOSE message. For F-G section: the calculation result shows that the Pearson similarity coefficient is 0.98 (very high similarity), and the transient waveform intensity difference coefficient is 0.02 p.u. (very small difference); for G-H section: the calculation result shows that the Pearson similarity coefficient is 0.65 (similarity drops sharply), and the transient waveform intensity difference coefficient is 0.40 p.u. (significant difference). The system starts the comprehensive judgment, the transient characteristics of F-G section are consistent, so it is not a fault section; the transient waveform and energy characteristics of G-H section are very different, and it is determined as the fault section boundary.

[0110] Through the comparison of multi-terminal data and multi-dimensional feature analysis, the ambiguity of the local judgment of G terminal is successfully excluded, and the fault is accurately segmented and locked in G-H line, avoiding misoperation or blind road pulling.

[0111] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for fault diagnosis of a primary and secondary integrated ring network box, characterized in that, include: The system collects the three-phase instantaneous voltage and instantaneous current signals of each feeder port in real time and converts them into digital transient data. Based on the moment of fault occurrence, digital transient data is preprocessed with a time window to extract zero-sequence waveform data. Perform wavelet packet decomposition on the zero-sequence waveform data to generate transient feature vectors; The transient zero-sequence power direction method extracts and integrates components from zero-sequence waveform data to generate polarity results. A pre-trained support vector machine (SVM) model is used to perform regression analysis and weighted summation on transient feature vectors, outputting a directional index. Local diagnostic results are generated based on the polarity results and the directional index. The specific process of the transient zero-sequence power direction method is as follows: digital filtering and differentiation are performed on the zero-sequence voltage and current of the zero-sequence waveform data to extract transient zero-sequence components. The differentiation is implemented using a low-delay digital differential filter. An instantaneous power algorithm is used to calculate the transient zero-sequence instantaneous power integral value of the transient zero-sequence components and determine the polarity result. A SVM model is used to perform regression analysis on the transient feature vectors, outputting a multi-frequency admittance feature vector with a dimension equal to the number of selected frequency bands. The SVM model uses a radial basis function as its kernel function and is trained based on different transient simulation data. Each component of the multi-frequency admittance feature vector is the complex ratio of the transient current signal to the transient voltage signal within the corresponding frequency band. The components of the multi-frequency admittance feature vector are weighted and summed to generate a directional index. The polarity result and the directional index are logically ANDed to generate a local diagnostic result, which includes a direction indication and a result type. When both the directional index and the polarity result clearly point to the same direction, the result type of the local diagnostic result is "can be isolated in place". If any one of the following conditions is met: the fault direction represented by the polarity result and the directional index is inconsistent, the reliability of the polarity result is lower than a preset reliability threshold, or the reliability of the directional index is lower than a preset reliability threshold, then the result type of the local diagnostic result is "cooperative positioning needs to be initiated". When the local diagnostic result indicates that collaborative positioning needs to be initiated, the ring network box requests the exchange of digital transient data with the adjacent ring network box terminals through the communication network; based on the digital transient data of the adjacent terminals, the transient current similarity coefficient and transient waveform intensity difference coefficient are calculated, and a comprehensive positioning result is generated by combining the local diagnostic result; The faulty line is determined based on the comprehensive positioning results, and a remote control command is generated; Fault isolation operations are performed based on remote control commands, and the PHM process is executed.

2. The method for fault diagnosis of a primary and secondary integrated ring network box according to claim 1, characterized in that, The specific process for generating the digital transient data is as follows: Three-phase instantaneous voltage and current signals are collected in real time by sensors integrated into the ring network enclosure; during the collection process, the three-phase instantaneous voltage and current signals are synchronized with hardware-level timestamps using a clock source, and the three-phase instantaneous voltage and current signals are digitized using an analog-to-digital converter (ADC) to generate digital transient data; the digital transient data is stored in RAM, and is locked and extracted using a fault transient triggering mechanism; The fault transient triggering mechanism is based on the detection of line current. When the absolute rate of change of zero-sequence current and / or zero-sequence voltage at any feeder port exceeds a threshold, the fault transient triggering mechanism will be triggered.

3. The method for fault diagnosis of a primary and secondary integrated ring network box according to claim 1, characterized in that, The specific generation method of the transient feature vector includes: selecting a preset time window before and after the fault occurrence time by locating the fault occurrence time; superimposing and calculating the instantaneous voltage and current of the three phases within the preset time window to extract zero-sequence waveform data containing instantaneous zero-sequence voltage and zero-sequence current; performing multi-level wavelet packet decomposition on the zero-sequence waveform data, wherein the multi-level wavelet packet decomposition uses a mother wavelet basis and sets the number of decomposition levels to divide the entire frequency band of the zero-sequence waveform data into multiple non-overlapping sub-frequency bands; and constructing a power distribution system using electromagnetic transient simulation software during the offline stage. The network simulation model simulates the fault mechanisms under different operating conditions and generates electromagnetic transient simulation results. Based on the electromagnetic transient simulation results, transient energy analysis is performed on each sub-band, and sub-bands are selected based on transient energy concentration and transient energy ratio. The wavelet packet energy value and cross-correlation coefficient of each selected sub-band are calculated, and all selected sub-bands are arranged in ascending order of frequency. The final transient feature vector consists of three parts: current energy sequence, voltage energy sequence, and voltage-current cross-correlation coefficient sequence arranged in ascending order of frequency.

4. The method for fault diagnosis of a primary and secondary integrated ring network box according to claim 1, characterized in that, The specific process of exchanging digital transient data is as follows: when the local diagnostic result determines that collaborative positioning needs to be initiated, a request instruction to exchange digital transient data is sent to the directly connected adjacent ring network box terminal through the communication network inside the distribution network; the request instruction requires that the digital transient data returned by the adjacent terminal be within the same time window of the fault occurrence time; the digital transient data is losslessly encoded through differential encoding.

5. The method for fault diagnosis of a primary and secondary integrated ring network box according to claim 1, characterized in that, The process of generating the comprehensive positioning result is as follows: After the ring network box receives the synchronous zero-sequence current waveform data of the adjacent terminal, it calculates the Pearson correlation coefficient between the zero-sequence current waveform of the current terminal and the zero-sequence current waveform of the adjacent terminal as the transient current similarity coefficient; at the same time, it calculates the transient waveform intensity difference coefficient between the waveforms of the current terminal and the adjacent terminal, where the transient waveform intensity difference coefficient is the absolute value of the difference between the transient waveform intensity index of the current terminal and the adjacent terminal, and the transient waveform intensity index is the integral of the square of the zero-sequence current waveform; the calculated transient current similarity coefficient and transient waveform intensity difference coefficient are logically judged with the local diagnostic results; if the transient current similarity coefficient is greater than the preset similarity threshold and the transient waveform intensity difference coefficient is less than the preset energy difference threshold, it is determined that there is no fault section boundary between the two terminals; if the transient current similarity coefficient is less than the preset energy difference threshold, it is determined that there is no fault section boundary between the two terminals; if the transient current similarity coefficient is less than the preset energy difference threshold, it is determined that there is no fault section boundary between the two terminals. If the similarity coefficient is less than a preset similarity threshold and the transient waveform intensity difference coefficient is greater than a preset energy difference threshold, then it is determined that there is a first type of candidate fault segment boundary between the two terminals; all remaining segments that do not belong to the above logical judgment are determined as second type of candidate fault segment boundaries; the ring network box determines the fault segment boundary by comparing the transient current similarity coefficient and transient waveform intensity difference coefficient of all adjacent segments and combining the direction indication of the local diagnostic results; the process of determining the fault segment boundary is as follows: excluding segments that are determined to have no fault segment boundary; using the first type of candidate fault segment boundary and the second type of candidate fault segment boundary as candidate boundaries, selecting the candidate boundary that matches the direction indication of the local diagnostic results as the fault segment boundary; generating a fault segment identifier based on the fault segment boundary, which is the comprehensive positioning result.

6. The method for fault diagnosis of a primary and secondary integrated ring network box according to claim 1, characterized in that, The specific process of performing fault isolation operation based on remote control command and executing PHM process is as follows: based on the comprehensive positioning results, the located section is mapped to the physical fault line by querying the distribution network topology and equipment connection table of the ring network box; The ring main unit generates remote control commands based on its built-in fault handling strategy model; Provided that the fault current has been cleared, the generated remote control command is sent directly to the circuit breaker intelligent operating mechanism integrated inside the ring main unit through the integrated digital interface, and the PHM process is started after the operation is completed. The PHM process is as follows: the ring main unit records the cumulative number of equipment operations, fault current level and operation timestamp, and generates fault operation data. A health degradation model for the equipment is constructed based on the cumulative number of operations and current stress. Based on fault operation data, the mechanical and electrical life consumption of the equipment is assessed through the health degradation model, and the equipment health status indicators and remaining service life are updated.

7. A primary and secondary integrated ring network box fault diagnosis system, characterized in that, include: The acquisition and sensing module is used to synchronously acquire the three-phase instantaneous voltage and instantaneous current signals of each feeder port in real time and convert them into digital transient data. The data processing and synchronization module performs time window preprocessing on the digitized transient data based on the time of the fault occurrence, extracts zero-sequence waveform data, and performs wavelet packet decomposition on the zero-sequence waveform data to generate transient feature vectors. The local diagnostic decision module is used to extract components and perform integral calculations on zero-sequence waveform data using the transient zero-sequence power direction method to generate polarity results; to perform regression analysis and weighted summation on transient feature vectors using a pre-trained support vector machine model to output directional indicators; and to generate local diagnostic results based on the polarity results and directional indicators. The specific process of the transient zero-sequence power direction method is as follows: digital filtering and differentiation processing are performed on the zero-sequence voltage and zero-sequence current of the zero-sequence waveform data to extract transient zero-sequence components; the differentiation processing is implemented using a low-delay digital differential filter; the transient zero-sequence instantaneous power integral value is calculated on the transient zero-sequence components using an instantaneous power algorithm, and the polarity result is determined; regression analysis is performed on the transient feature vectors using a support vector machine model to output multi-frequency admittance feature vectors with dimensions equal to the number of selected frequency bands; the support vector machine model uses radial basis functions as kernel functions and is trained based on different transient simulation data; each component of the multi-frequency admittance feature vector is the complex ratio of the transient current signal to the transient voltage signal within the corresponding frequency band. The components of the multi-frequency admittance feature vector are weighted and summed to generate a directional index. The polarity result and the directional index are logically ANDed to generate a local diagnostic result, which includes a direction indication and a result type. When both the directional index and the polarity result clearly point to the same direction, the result type of the local diagnostic result is "can be isolated in place". If any one of the following conditions is met: the fault direction represented by the polarity result and the directional index is inconsistent, the reliability of the polarity result is lower than a preset reliability threshold, or the reliability of the directional index is lower than a preset reliability threshold, then the result type of the local diagnostic result is "cooperative positioning needs to be initiated". When the local diagnostic result indicates that collaborative positioning needs to be initiated, the collaborative positioning and control execution module requests the exchange of digital transient data with the adjacent ring network box terminals through the communication network; it calculates the transient current similarity coefficient and transient waveform intensity difference coefficient based on the digital transient data of the adjacent terminals, and generates a comprehensive positioning result by combining the local diagnostic result; The faulty line is determined based on the comprehensive positioning results, and a remote control command is generated; Fault isolation operations are performed based on remote control commands, and the PHM process is executed.

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