A fault monitoring system and method based on electrical equipment operation

Abstract

The application discloses a kind of based on the fault monitoring system and method of electrical equipment operation, it is related to fault monitoring technical field, monitoring system includes signal monitoring module, signal processing module, fault analysis module and database;Method includes: first according to the failure mechanism of electrical equipment, the fault mechanism characteristic fingerprint of each early fault of electrical equipment is determined, second according to the fault mechanism characteristic fingerprint of each early fault selects the signal needing to be filtered, obtains the operating signal of electrical equipment, after judging whether electrical equipment is running fault, if running fault, then according to the switching operation of power grid updates the topological structure of power grid and the characteristic fingerprint of branch reflected wave, then distinguish fault traveling wave and branch reflected wave, carry out fault location.The application can accurately distinguish fault traveling wave and branch reflected wave, guarantee the effectiveness of fault analysis, also guarantee the accuracy of fault location.

Description

Technical Field

[0001] This invention relates to the field of fault monitoring technology, and specifically to a fault monitoring system and method based on the operation of electrical equipment. Background Technology

[0002] With the deepening of smart grid construction, the high proportion of new energy connected to the grid and the continuous expansion of the power distribution network, the safe and stable operation of electrical equipment has become the core foundation for ensuring power supply reliability. The electrical equipment of the power distribution system is in a complex operating environment with strong electromagnetic fields, load fluctuations and temperature and humidity changes for a long time, which makes it prone to faults such as insulation aging, poor contact and mechanical jamming. If these faults cannot be identified and dealt with in advance, they will cause safety accidents such as equipment burnout and large-scale power outages.

[0003] Existing fault monitoring systems and methods based on the operation of electrical equipment filter and remove noise from the collected signals to determine whether the electrical equipment is faulty. If the electrical equipment is faulty, the fault traveling wave and branch reflected wave are distinguished according to the prior parameters of the power grid topology. Obviously, such fault monitoring systems and methods based on the operation of electrical equipment have at least the following shortcomings: 1. Existing technologies filter and remove noise from all collected signals. However, in the early stage of a fault, the early fault signal and the noise signal have the same characteristics. When filtering, the early fault signal is easily removed, which leads to a decrease in the fidelity of the electrical equipment signal characteristics and thus cannot guarantee the effectiveness of the fault analysis.

[0004] 2. Existing technologies distinguish between fault traveling waves and branch reflected waves based on prior parameters of the power grid topology. However, during operation, the topology of the power grid may change due to switching operations. Existing technologies cannot update the prior parameters of the power grid topology based on switching operations, and changes in the power grid topology will also cause changes in the characteristics of branch reflected waves. Therefore, existing technologies cannot accurately distinguish between fault traveling waves and branch reflected waves, and thus cannot guarantee the accuracy of fault location. Summary of the Invention

[0005] In view of the above-mentioned technical deficiencies, the purpose of this invention is to provide a fault monitoring system and method based on the operation of electrical equipment.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: a fault monitoring system based on the operation of electrical equipment, comprising: The signal monitoring module is used to set monitoring times and monitor the operation of electrical equipment at each monitoring time. The signal processing module is used to build a fault mechanism feature fingerprint database for electrical equipment. Based on the fault mechanism feature fingerprint database of electrical equipment, the collected signals are processed to obtain the operating signals of electrical equipment. The fault analysis module is used to acquire the operating signals of electrical equipment, determine whether the electrical equipment is malfunctioning, and when the electrical equipment is malfunctioning, it distinguishes between fault traveling waves and branch reflected waves, and locates the fault. The database is used to store the failure mechanisms of electrical equipment, the topology of the power grid, and switching operation tables.

[0007] Furthermore, the signal processing module includes a fault mechanism feature fingerprint database construction unit and a filtering processing unit; The fault mechanism feature fingerprint database construction unit is used to simulate each early fault of electrical equipment multiple times, determine the fault mechanism feature fingerprint of each early fault of electrical equipment, and store each early fault and its fault mechanism feature fingerprint one-to-one to form a fault mechanism feature fingerprint database. The filtering unit is used to acquire the collected signals, match them with the fault mechanism feature fingerprint database, identify early fault signals in the signals, and filter other signals.

[0008] Furthermore, the specific execution process for determining the fault mechanism feature fingerprints of each early fault of the electrical equipment is as follows: A11. Simulate each early fault of the electrical equipment multiple times, obtain each set of signals of the electrical equipment under each early fault, and obtain the failure mechanism of the electrical equipment from the database. A12. Under a certain early fault, based on the failure mechanism of the electrical equipment, determine the potential signal of the early fault, extract the potential signals of the electrical equipment under the early fault from the various sets of signals of the electrical equipment under the early fault, and extract the fault mechanism feature fingerprint of the electrical equipment under the early fault based on the various sets of potential signals of the electrical equipment under the early fault. A13. Repeat step A12 to obtain the fault mechanism feature fingerprints of each early fault of the electrical equipment.

[0009] Furthermore, the filtering processing unit performs the following specific steps: The collected signals are acquired and matched with the fault mechanism feature fingerprint database to determine whether the match is successful. If a match is successful, the signal that matches the fault mechanism feature fingerprint among the collected signals is called the early fault signal, and the other signals are called the signals to be processed. At this time, only the signals to be processed are filtered, the early fault signal is retained, and the filtered signals to be processed and the early fault signals are used as the operating signals of the electrical equipment. If a match fails, all collected signals will be filtered, and the processed signals will be used as the operating signals of the electrical equipment.

[0010] Furthermore, the fault analysis module includes an operation judgment unit, a traveling wave identification unit, and a fault location unit; The operation judgment unit is used to determine whether the operation of the electrical equipment is faulty based on the operation signal of the electrical equipment; The traveling wave identification unit is used to monitor the switching operation of the power grid in real time when the electrical equipment malfunctions, and to distinguish between the fault traveling wave and the branch reflected wave based on the switching operation of the power grid. The fault location unit is used to acquire the fault traveling wave and locate the fault based on the fault traveling wave.

[0011] Furthermore, the traveling wave recognition unit performs the following process: Real-time reading of power grid switching operations; when power grid switching operations change, determine whether the power grid topology has changed. When the topology of the power grid changes, A21, update the power grid topology stored in the database; A22. Based on the updated power grid topology, determine the monitoring points of the power grid, and at the same time, update the characteristic fingerprint of the branch reflected wave on the label of the monitoring point according to the power grid topology in the database. A23. When the monitoring point detects an electromagnetic wave, it acquires the electromagnetic wave signal and extracts the electromagnetic wave features from it. The electromagnetic wave features are then matched with the branch reflection wave feature fingerprint of the tag on the monitoring point. If the match is successful, it means that the electromagnetic wave is a branch reflection wave; otherwise, it means that the electromagnetic wave is a fault traveling wave. When the topology of the power grid remains unchanged, the fault traveling wave and branch reflected wave are distinguished according to the methods in steps A22 to A23.

[0012] Furthermore, the specific execution process for determining whether the topology of the power grid has changed is as follows: The read power grid switching operation is matched with the switching operation table stored in the database. If the match is successful, it means that the switching operation will cause a change in the power grid topology. If the match fails, it means that the switching operation will not cause a change in the power grid topology.

[0013] Furthermore, the specific execution process for updating the power grid topology stored in the database is as follows: Retrieve the grid topology stored in the database before the grid performs the switching operation, and call it the marked grid topology. The grid switching operation is called the marked switching operation. A simulation platform is built to simulate the marked power grid topology and the marked switching operation on the marked power grid topology. The simulated power grid topology map is then obtained and updated in the database.

[0014] To better achieve the objectives of this invention, this invention also provides a fault monitoring system based on the operation of electrical equipment, wherein the specific execution process of updating the characteristic fingerprint of the branch reflected wave is as follows: A31. Based on the updated power grid topology, obtain each branch connected to the monitoring point, and determine the marked topology area based on the branch where the monitoring point is located and each branch connected to the monitoring point. A32. In the simulation platform, perform multiple normal operation simulations on the marked topological structure region, obtain electromagnetic wave signals during each simulation, and extract electromagnetic wave features based on the electromagnetic wave signals during each simulation. A33. Use the characteristics of electromagnetic waves as the characteristic fingerprints of branched reflected waves and update the tag at the monitoring point accordingly.

[0015] Meanwhile, the present invention also provides a fault monitoring method based on a fault monitoring system for the operation of electrical equipment. Applying the system described in this invention, the method includes: S1. Signal monitoring: Set monitoring times and monitor the operation of electrical equipment at each monitoring time; S2. Signal Processing: Construct a fault mechanism feature fingerprint database for electrical equipment, and process the collected signals based on the fault mechanism feature fingerprint database to obtain the operating signals of the electrical equipment; S3. Fault Analysis: Obtain the operating signals of electrical equipment, determine whether the operation of electrical equipment is faulty, and when the operation of electrical equipment is faulty, distinguish between fault traveling waves and branch reflected waves, and locate the fault.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention provides a fault monitoring system and method based on the operation of electrical equipment. First, based on the failure mechanism of the electrical equipment, the fault mechanism feature fingerprint of each early fault of the electrical equipment is determined. Second, based on the fault mechanism feature fingerprint of each early fault, the signal to be filtered is selected to obtain the operating signal of the electrical equipment. Then, it is determined whether the electrical equipment is operating faulty. If it is operating faulty, the topology of the power grid and the feature fingerprint of the branch reflection wave are updated according to the switching operation of the power grid. Then, the fault traveling wave and the branch reflection wave are distinguished and the fault is located. It can accurately distinguish the fault traveling wave and the branch reflection wave, ensuring the effectiveness of fault analysis and the accuracy of fault location.

[0017] This invention simulates various early faults of electrical equipment multiple times, acquires data sets for each early fault, retrieves the failure mechanism of the equipment from a database, identifies potential signals for each early fault, extracts these potential signals from the database, and extracts fault mechanism feature fingerprints for each early fault, constructing a fault mechanism feature fingerprint database. The acquired signals are matched against this database. If a match is successful, the signal matching the fault mechanism feature fingerprint is designated as an early fault signal, and the other signals are designated as signals to be processed. Only the signals to be processed are filtered, retaining the early fault signals. If a match fails, all acquired signals are filtered, improving the fidelity of the electrical equipment signal characteristics and ensuring the effectiveness of fault analysis.

[0018] This invention reads the switching operations of the power grid in real time. When the switching operations of the power grid change, it determines whether the topology of the power grid has changed. If the topology of the power grid changes, it updates the power grid topology stored in the database. Based on the updated power grid topology, it determines the monitoring point of the power grid. At the same time, the tag on the monitoring point updates the characteristic fingerprint of the branch reflected wave according to the power grid topology in the database. When the monitoring point detects an electromagnetic wave, it acquires the electromagnetic wave signal and extracts the electromagnetic wave characteristics. It matches the electromagnetic wave characteristics with the branch reflected wave characteristic fingerprint of the tag on the monitoring point. If the match is successful, it means that the electromagnetic wave is a branch reflected wave; otherwise, it means that the electromagnetic wave is a fault traveling wave. When the topology of the power grid has not changed, the above method is used to distinguish between fault traveling waves and branch reflected waves, which can accurately distinguish between fault traveling waves and branch reflected waves and ensure the accuracy of fault location. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0021] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1: Please refer to Figure 1 As shown, the present invention provides a fault monitoring system based on the operation of electrical equipment, including: a signal monitoring module, a signal processing module, a fault analysis module, and a database.

[0024] The signal monitoring module is connected to the signal processing module, the signal processing module is connected to the fault analysis module, and the database is connected to both the signal processing module and the fault analysis module.

[0025] The signal monitoring module is used to set various monitoring times and to detect the operation of electrical equipment at each monitoring time.

[0026] It should be noted that each monitoring time is set according to a preset time interval, which is set by the staff based on the daily operation of the power equipment.

[0027] The signal processing module is used to construct a fault mechanism feature fingerprint database for electrical equipment. Based on the fault mechanism feature fingerprint database of electrical equipment, the collected signals are processed to obtain the operating signals of the electrical equipment.

[0028] It should be noted that the acquired signals include pulses, phase, peak power frequency voltage, temperature, resistance, and current. These signals are acquired using instruments such as high-speed oscilloscopes, phase detectors, peak voltmeters, fiber optic temperature sensors, insulation resistance testers, and current transformers.

[0029] In one specific embodiment, the signal processing module includes a fault mechanism feature fingerprint database construction unit and a filtering processing unit.

[0030] The fault mechanism feature fingerprint database construction unit is used to simulate each early fault of the electrical equipment multiple times, determine the fault mechanism feature fingerprint of each early fault of the electrical equipment, and store each early fault and its fault mechanism feature fingerprint one-to-one to form a fault mechanism feature fingerprint database.

[0031] It should be noted that electrical equipment faults include insulation degradation, high-resistance grounding in the power distribution network, and poor contact at cable joints. Among these, early-stage faults refer to those occurring in the initial stage, before the fault characteristics have become apparent.

[0032] It should also be noted that, since the failure mechanisms of each early fault are different, the failure mechanism characteristic fingerprint of each early fault is unique. Based on the uniqueness of the failure mechanism characteristic fingerprint of each early fault, the collected signal processing and fault analysis can be carried out in the subsequent process.

[0033] Among them, the failure mechanisms corresponding to different early faults are different. Taking early insulation degradation as an example, its failure mechanism is: the rising edge of the partial discharge pulse is always <10ns, and the pulse phase is strictly bound to the peak range of the power frequency voltage (positive half-cycle peak / negative half-cycle peak, which is determined by the field strength threshold of the air gap electric field breakdown).

[0034] In a specific embodiment, the process of determining the failure mechanism feature fingerprint of each early fault of the electrical equipment is as follows: A11. Perform multiple simulations on each early fault of the electrical equipment to obtain each set of signals of the electrical equipment under each early fault, and obtain the failure mechanism of the electrical equipment from the database.

[0035] It should be noted that the failure of electrical equipment refers to the process in which, under the long-term action of four types of stress—electricity, heat, machinery, and environment—the insulation, conductivity, and mechanical structure gradually deteriorate, eventually losing their original functions such as conductivity, insulation, arc extinguishing, and support, leading to faults such as short circuits, open circuits, overheating, and breakdowns.

[0036] A12. Under a certain early fault, based on the failure mechanism of the electrical equipment, determine the potential signal of the early fault, extract the potential signals of the electrical equipment under the early fault from the various sets of signals of the electrical equipment under the early fault, and extract the fault mechanism feature fingerprint of the electrical equipment under the early fault based on the various sets of potential signals of the electrical equipment under the early fault.

[0037] It should be noted that the hidden danger signals are determined from the failure mechanism of early faults. Taking early insulation deterioration as an example, the hidden danger signals are pulses, phases, and power frequency voltage peaks.

[0038] It should also be noted that the failure mechanism feature fingerprint is extracted by Transformer, which is an existing technology. The specific process is as follows: smoothing and normalizing each group of potential hazard signals, and building the embedding layer, position encoding layer, encoder, decoder, output layer and loss function of Transformer. Each potential hazard signal is obtained from the database, and each potential hazard signal and the failure mechanism of electrical equipment are divided into training set, test set and validation set to train Transformer. After training, the processed groups of potential hazard signals are input into Transformer, and the failure mechanism feature fingerprint is output.

[0039] In this context, the failure mechanism of electrical equipment is bound to the training set, test set, and verification set as a constraint.

[0040] A13. Repeat step A12 to obtain the fault mechanism feature fingerprints of each early fault of the electrical equipment.

[0041] The filtering unit is used to acquire the collected signals, match them with the fault mechanism feature fingerprint database, identify early fault signals in the signals, and filter other signals.

[0042] In a specific embodiment, the filtering processing unit performs the following process: acquiring the collected signal and matching it with the fault mechanism feature fingerprint database to determine whether the match is successful.

[0043] It should be noted that the collected signals are matched with the fault mechanism feature fingerprint database using quantum algorithms.

[0044] If a match is successful, the signal that matches the fault mechanism feature fingerprint among the collected signals is called the early fault signal, and the other signals are called the signals to be processed. At this time, only the signals to be processed are filtered, the early fault signals are retained, and the filtered signals to be processed and the early fault signals are used as the operating signals of the electrical equipment.

[0045] If a match fails, all collected signals will be filtered, and the processed signals will be used as the operating signals of the electrical equipment.

[0046] The fault analysis module is used to acquire the operating signals of electrical equipment, determine whether the operation of the electrical equipment is faulty, and when the electrical equipment is faulty, distinguish between fault traveling waves and branch reflected waves, and locate the fault.

[0047] In one specific embodiment, the fault analysis module includes an operation judgment unit, a traveling wave identification unit, and a fault location unit.

[0048] The operation judgment unit is used to determine whether the operation of the electrical equipment is faulty based on the operation signal of the electrical equipment.

[0049] It should be noted that the operating signals of the electrical equipment are acquired, and the characteristics of the operating signals are obtained. The operating signal characteristics of the electrical equipment are compared with the characteristics of various operating fault signals stored in the database. If the operating signal characteristics of the electrical equipment are the same as a certain operating fault signal characteristic, it means that the electrical equipment is operating faulty; otherwise, it means that the electrical equipment is operating normally.

[0050] Specifically, the Transformer is used to acquire the operating signal characteristics and various operational fault signal characteristics of the electrical equipment. It's important to understand that by simulating various faults in the electrical equipment during operation, the operating signals of the equipment under different fault conditions are obtained, and based on these operating signals, the characteristics of each operational fault signal are extracted.

[0051] The traveling wave identification unit is used to monitor the switching operation of the power grid in real time when the electrical equipment malfunctions, and to distinguish between the fault traveling wave and the branch reflected wave based on the switching operation of the power grid.

[0052] It should be noted that the switching operations of the power grid are read from the power grid's operation log. It is important to understand that the power grid read is the one where the electrical equipment is located.

[0053] Among them, the switching operations of the power grid include line power outage and restoration operations, loop disconnection operations, double busbar switching operations, main transformer voltage regulation operations, neutral point grounding operations, and auxiliary equipment commissioning and decommissioning.

[0054] In a specific embodiment, the traveling wave identification unit performs the following process: real-time reading of the switching operations of the power grid, and when the switching operations of the power grid change, determining whether the topology of the power grid has changed.

[0055] When the power grid topology changes, A21, update the power grid topology stored in the database; A22, determine the monitoring points of the power grid based on the updated power grid topology, and update the characteristic fingerprint of the branch reflection wave on the tag at the monitoring point according to the power grid topology in the database; A23, when the monitoring point detects an electromagnetic wave, acquire the electromagnetic wave signal, extract the electromagnetic wave characteristics from it, and match the electromagnetic wave characteristics with the branch reflection wave characteristic fingerprint of the tag at the monitoring point. If the match is successful, it means that the electromagnetic wave is a branch reflection wave; otherwise, it means that the electromagnetic wave is a fault traveling wave.

[0056] It should be noted that the updated power grid topology is obtained, and based on the updated power grid topology, the energized branches are selected, and monitoring points are set up on these branches.

[0057] It is important to know that electromagnetic wave signals are monitored through a traveling wave ranging device on power distribution lines.

[0058] It should also be noted that the modal coupling characteristics of electromagnetic wave signals are extracted and obtained through phase mode transformation decoupling.

[0059] Specifically, if the electromagnetic wave feature is the same as the branch reflection wave feature fingerprint of the tag at the monitoring point, it means that the match is successful; otherwise, it means that the match is unsuccessful.

[0060] When the topology of the power grid remains unchanged, fault traveling waves and branch reflected waves are distinguished according to the methods in steps A22-A23.

[0061] It should be noted that when the topology of the power grid remains unchanged, the branch reflection wave characteristic fingerprint of the tag at the monitoring point will not be updated.

[0062] The specific process for determining whether the power grid topology has changed is as follows: the read power grid switching operation is matched with the switching operation table stored in the database. If the match is successful, it means that the switching operation will cause a change in the power grid topology. If the match fails, it means that the switching operation will not cause a change in the power grid topology.

[0063] It should be noted that the switching operation table is used to store switching operations that can change the power grid topology. These switching operations include line power outage and restoration operations, loop disconnection operations, and double busbar switching operations.

[0064] The specific process of updating the power grid topology stored in the database is as follows: obtain the power grid topology stored in the database before the power grid performs the switching operation, and call it the marked power grid topology. The switching operation of the power grid is called the marked switching operation.

[0065] A simulation platform is built to simulate the marked power grid topology and the marked switching operation on the marked power grid topology. The simulated power grid topology map is then obtained and updated in the database.

[0066] It should be noted that the simulation software used to build the simulation platform is determined by the designers.

[0067] The specific process of updating the characteristic fingerprint of the branch reflection wave is as follows: A31. Based on the updated power grid topology, obtain each branch connected to the monitoring point, and determine the marked topology region based on the branch where the monitoring point is located and each branch connected to the monitoring point.

[0068] It should be noted that the area where the monitoring point is located and the area of ​​each branch connected to the monitoring point in the topology diagram are called the marked topology structure area.

[0069] A32. In the simulation platform, perform multiple normal operation simulations on the marked topological structure region, obtain electromagnetic wave signals during each simulation, and extract electromagnetic wave features based on the electromagnetic wave signals during each simulation.

[0070] A33. Use the electromagnetic wave characteristics as the characteristic fingerprint of the branched reflected wave and update the tag at the monitoring point.

[0071] The fault location unit is used to acquire the fault traveling wave and locate the fault based on the fault traveling wave.

[0072] It should be noted that fault location is achieved by measuring the propagation speed of the fault traveling wave and the time it takes for the fault traveling wave to reach both ends of the circuit branch.

[0073] The database is used to store the failure mechanisms of electrical equipment, the topology of the power grid, and switching operation tables.

[0074] Please see Figure 2 As shown, the present invention provides a fault monitoring method based on the operation of electrical equipment, including: S1, signal monitoring: setting various monitoring times, and detecting the operation of electrical equipment at each monitoring time.

[0075] S2. Signal Processing: Construct a fault mechanism feature fingerprint database for electrical equipment. Based on the fault mechanism feature fingerprint database of electrical equipment, process the collected signals to obtain the operating signals of electrical equipment.

[0076] S3. Fault Analysis: Obtain the operating signals of electrical equipment, determine whether the operation of electrical equipment is faulty, and when the operation of electrical equipment is faulty, distinguish between fault traveling waves and branch reflected waves, and locate the fault.

[0077] This invention first determines the fault mechanism feature fingerprints of each early fault of the electrical equipment based on the failure mechanism of the electrical equipment. Then, it selects the signals to be filtered based on the fault mechanism feature fingerprints of each early fault to obtain the operating signals of the electrical equipment. After that, it determines whether the electrical equipment is operating faulty. If it is operating faulty, it updates the topology of the power grid and the feature fingerprints of the branch reflected waves based on the switching operation of the power grid. Then, it distinguishes between the fault traveling waves and the branch reflected waves to locate the fault. It can accurately distinguish between the fault traveling waves and the branch reflected waves, ensuring the effectiveness of the fault analysis and the accuracy of the fault location.

[0078] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A fault monitoring system based on the operation of electrical equipment, characterized in that, include: The signal monitoring module is used to set monitoring times and monitor the operation of electrical equipment at each monitoring time. The signal processing module is used to build a fault mechanism feature fingerprint database for electrical equipment. Based on the fault mechanism feature fingerprint database of electrical equipment, the collected signals are processed to obtain the operating signals of electrical equipment. The fault analysis module is used to acquire the operating signals of electrical equipment, determine whether the electrical equipment is malfunctioning, and when the electrical equipment is malfunctioning, it distinguishes between fault traveling waves and branch reflected waves, and locates the fault. The database is used to store the failure mechanisms of electrical equipment, the topology of the power grid, and switching operation tables.

2. The fault monitoring system based on the operation of electrical equipment according to claim 1, characterized in that, The signal processing module includes a fault mechanism feature fingerprint database construction unit and a filtering processing unit; The fault mechanism feature fingerprint database construction unit is used to simulate each early fault of electrical equipment multiple times, determine the fault mechanism feature fingerprint of each early fault of electrical equipment, and store each early fault and its fault mechanism feature fingerprint one-to-one to form a fault mechanism feature fingerprint database. The filtering unit is used to acquire the collected signals, match them with the fault mechanism feature fingerprint database, identify early fault signals in the signals, and filter other signals.

3. A fault monitoring system based on the operation of electrical equipment according to claim 2, characterized in that, The specific execution process for determining the fault mechanism feature fingerprints of each early fault of electrical equipment is as follows: A11. Simulate each early fault of the electrical equipment multiple times, obtain each set of signals of the electrical equipment under each early fault, and obtain the failure mechanism of the electrical equipment from the database. A12. Under a certain early fault, based on the failure mechanism of the electrical equipment, determine the potential signal of the early fault, extract the potential signals of the electrical equipment under the early fault from the various sets of signals of the electrical equipment under the early fault, and extract the fault mechanism feature fingerprint of the electrical equipment under the early fault based on the various sets of potential signals of the electrical equipment under the early fault. A13. Repeat step A12 to obtain the fault mechanism feature fingerprints of each early fault of the electrical equipment.

4. A fault monitoring system based on the operation of electrical equipment according to claim 2, characterized in that, The specific execution process of the filtering unit is as follows: The collected signals are acquired and matched with the fault mechanism feature fingerprint database to determine whether the match is successful. If a match is successful, the signal that matches the fault mechanism feature fingerprint among the collected signals is called the early fault signal, and the other signals are called the signals to be processed. At this time, only the signals to be processed are filtered, the early fault signal is retained, and the filtered signals to be processed and the early fault signals are used as the operating signals of the electrical equipment. If a match fails, all collected signals will be filtered, and the processed signals will be used as the operating signals of the electrical equipment.

5. A fault monitoring system based on the operation of electrical equipment according to claim 1, characterized in that, The fault analysis module includes an operation judgment unit, a traveling wave identification unit, and a fault location unit. The operation judgment unit is used to determine whether the operation of the electrical equipment is faulty based on the operation signal of the electrical equipment; The traveling wave identification unit is used to monitor the switching operation of the power grid in real time when the electrical equipment malfunctions, and to distinguish between the fault traveling wave and the branch reflected wave based on the switching operation of the power grid. The fault location unit is used to acquire the fault traveling wave and locate the fault based on the fault traveling wave.

6. A fault monitoring system based on the operation of electrical equipment according to claim 5, characterized in that, The traveling wave recognition unit performs the following process: Real-time reading of power grid switching operations; when power grid switching operations change, determine whether the power grid topology has changed. When the topology of the power grid changes, A21, update the power grid topology stored in the database; A22. Based on the updated power grid topology, determine the monitoring points of the power grid, and at the same time, update the characteristic fingerprint of the branch reflected wave on the label of the monitoring point according to the power grid topology in the database. A23. When the monitoring point detects an electromagnetic wave, it acquires the electromagnetic wave signal and extracts the electromagnetic wave features from it. The electromagnetic wave features are then matched with the branch reflection wave feature fingerprint of the tag on the monitoring point. If the match is successful, it means that the electromagnetic wave is a branch reflection wave; otherwise, it means that the electromagnetic wave is a fault traveling wave. When the topology of the power grid remains unchanged, the fault traveling wave and branch reflected wave are distinguished according to the methods in steps A22 to A23.

7. A fault monitoring system based on the operation of electrical equipment according to claim 6, characterized in that, The specific execution process for determining whether the topology of the power grid has changed is as follows: The read power grid switching operation is matched with the switching operation table stored in the database. If the match is successful, it means that the switching operation will cause a change in the power grid topology. If the match fails, it means that the switching operation will not cause a change in the power grid topology.

8. A fault monitoring system based on the operation of electrical equipment according to claim 6, characterized in that, The specific execution process for updating the power grid topology stored in the database is as follows: Retrieve the grid topology stored in the database before the grid performs the switching operation, and call it the marked grid topology. The grid switching operation is called the marked switching operation. A simulation platform is built to simulate the marked power grid topology and the marked switching operation on the marked power grid topology. The simulated power grid topology map is then obtained and updated in the database.

9. A fault monitoring system based on the operation of electrical equipment according to claim 6, characterized in that, The specific execution process for updating the characteristic fingerprint of the branch reflection wave is as follows: A31. Based on the updated power grid topology, obtain each branch connected to the monitoring point, and determine the marked topology area based on the branch where the monitoring point is located and each branch connected to the monitoring point. A32. In the simulation platform, perform multiple normal operation simulations on the marked topological structure region, obtain electromagnetic wave signals during each simulation, and extract electromagnetic wave features based on the electromagnetic wave signals during each simulation. A33. Use the characteristics of electromagnetic waves as the characteristic fingerprints of branched reflected waves and update the tag at the monitoring point accordingly.

10. A fault monitoring method for a fault monitoring system based on the operation of electrical equipment, characterized in that, The method, using the system according to any one of claims 1-9, comprises: S1. Signal monitoring: Set monitoring times and monitor the operation of electrical equipment at each monitoring time; S2. Signal Processing: Construct a fault mechanism feature fingerprint database for electrical equipment, and process the collected signals based on the fault mechanism feature fingerprint database to obtain the operating signals of the electrical equipment; S3. Fault Analysis: Obtain the operating signals of electrical equipment, determine whether the operation of electrical equipment is faulty, and when the operation of electrical equipment is faulty, distinguish between fault traveling waves and branch reflected waves, and locate the fault.

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