Fault detection method and device for booster station, electronic equipment and storage medium

Abstract

The invention discloses a booster station fault detection method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the main technical scheme comprises the steps: obtaining the electrical quantity data of a to-be-detected target; inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model; and sending the electronic quantity data and the fault information to a scheduling end for storage under the condition that the existence of the fault information is determined in the fault judgment result. The electrical quantity data of the to-be-detected target is acquired and input into the preset fault detection model, and detection is performed through the preset fault detection model so as to judge whether the to-be-detected target has a fault or not. The efficiency and accuracy of fault detection are improved, and timely response can be ensured when a fault occurs. Meanwhile, the electronic quantity data containing the fault information is sent to the scheduling end to be stored, so that subsequent fault analysis and processing are facilitated.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a fault detection method and device for a booster station, an electronic device, and a storage medium. Background Art

[0002] Vigorously developing low-carbon or zero-carbon energy systems such as renewable energy and building a new power system with new energy as the main body has become the strategic direction of technological change in the energy field. Among them, photovoltaic power generation is a recognized renewable, green and clean energy with the advantages of huge energy source, environmental protection and pollution-free, safety and sustainability.

[0003] As the power collection center of the photovoltaic power generation field, the inspection and operation of the booster station is crucial to ensure the safe production and efficiency improvement of the power plant. At present, the fault detection of the booster station still relies on manual inspection, but this method has a time lag, resulting in untimely fault detection, which will affect the power generation efficiency of the photovoltaic power station. Summary of the invention

[0004] The present disclosure provides a booster station fault detection method, device, electronic device and storage medium, the main purpose of which is to achieve automatic detection of booster station faults.

[0005] According to a first aspect of the present disclosure, a fault detection method for a booster station is provided, comprising:

[0006] Acquire electrical quantity data of the target to be detected;

[0007] Inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model;

[0008] When it is determined that fault information exists in the fault judgment result, the electronic quantity data and the fault information are sent to the dispatching end for storage.

[0009] Optionally, after inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model, the method further includes:

[0010] When it is determined in the fault judgment result that there is no fault information, the target to be detected is re-detected according to a preset time threshold based on the preset fault detection model.

[0011] Optionally, before inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model, the method further includes:

[0012] Acquire training electrical quantity data of the target to be detected; wherein the training electrical quantity data includes abnormal data and normal data;

[0013] The preset fault detection model is trained according to the training electrical consumption data, and when the loss function of the preset fault detection model is less than or equal to a preset threshold, the training is stopped to obtain a trained preset fault detection model.

[0014] Optionally, the training electrical quantity data includes operating electrical quantity data and switching electrical quantity data.

[0015] Optionally, when it is determined that there is fault information in the fault judgment result, sending the electronic quantity data and the fault information to the dispatching end for storage further includes:

[0016] The fault information is broadcast according to the preset alarm mode.

[0017] According to a second aspect of the present disclosure, there is provided a fault detection device for a booster station, comprising:

[0018] A first acquisition unit, used to acquire electrical quantity data of a target to be detected;

[0019] A judgment unit, used for inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model;

[0020] A sending unit is used to send the electronic quantity data and the fault information to the dispatching end for storage when it is determined that there is fault information in the fault judgment result.

[0021] Optionally, the device further comprises:

[0022] The detection unit is used to re-detect the target to be detected based on the preset fault detection model according to the preset time threshold after the judgment unit inputs the electrical quantity data into the preset fault detection model to obtain the fault judgment result output by the preset fault detection model, if it is determined that there is no fault information in the fault judgment result.

[0023] Optionally, the device further comprises:

[0024] A second acquisition unit is used to acquire training electrical quantity data of the target to be detected before the judgment unit inputs the electrical quantity data into a preset fault detection model to obtain the fault judgment result output by the preset fault detection model; wherein the training electrical quantity data includes abnormal data and normal data;

[0025] A training unit is used to train the preset fault detection model according to the training electrical quantity data, and stop the training when the loss function of the preset fault detection model is less than or equal to a preset threshold, so as to obtain a trained preset fault detection model.

[0026] Optionally, the training electrical quantity data includes operating electrical quantity data and switching electrical quantity data.

[0027] Optionally, the sending unit is further used for:

[0028] The fault information is broadcast according to the preset alarm mode.

[0029] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0030] at least one processor; and

[0031] a memory communicatively connected to the at least one processor; wherein,

[0032] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0033] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0034] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0035] The fault detection method, device, electronic device and storage medium of the booster station provided by the present disclosure mainly include the following technical solutions: obtaining the electrical quantity data of the target to be detected; inputting the electrical quantity data into a preset fault detection model to obtain the fault judgment result output by the preset fault detection model; when it is determined that there is fault information in the fault judgment result, sending the electrical quantity data and the fault information to the dispatching end for storage. Compared with the related art, the embodiment of the present application obtains the electrical quantity data of the target to be detected and inputs it into a preset fault detection model, and performs detection through the preset fault detection model to determine whether a fault occurs in the target to be detected. The efficiency and accuracy of fault detection are improved, and timely response is ensured when a fault occurs. At the same time, the electronic quantity data containing the fault information is sent to the dispatching end for storage, which is helpful for subsequent fault analysis and processing.

[0036] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0038] Figure 1 A schematic flow chart of a fault detection method for a booster station provided in an embodiment of the present disclosure;

[0039] Figure 2 A schematic flow chart of a fault detection method for a booster station provided in an embodiment of the present disclosure;

[0040] Figure 3 A schematic structural diagram of a fault detection device for a booster station provided in an embodiment of the present disclosure;

[0041] Figure 4 A schematic structural diagram of a fault detection device for a booster station provided in an embodiment of the present disclosure;

[0042] Figure 5 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0044] The following describes a fault detection method, device, electronic device, and storage medium for a booster station according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0045] Figure 1 A schematic flow chart of a fault detection method for a booster station provided in an embodiment of the present disclosure.

[0046] like Figure 1 As shown, the method comprises the following steps:

[0047] Step 101, obtaining electrical quantity data of a target to be detected.

[0048] In some embodiments, the electrical quantity data can be determined based on actual needs to include specific data items, such as three-phase current, zero-sequence current, three-phase voltage, zero-sequence voltage, protection action time, power and frequency changes, etc. The electrical quantity data to be collected can be determined based on the type of target to be detected. Specifically, the embodiments of the present application do not limit the specific content and values ​​of the electrical quantity data.

[0049] In some embodiments, when collecting data, it can be based on sensor measurement, smart meter reading, or remote monitoring system collection. Specifically, it can be determined according to actual needs, and the embodiments of the present application are not limited to this.

[0050] In some embodiments, there may be multiple targets to be detected, such as transformers, transmission lines, generators, etc. Specifically, the embodiments of the present application do not limit the number and types of targets to be detected.

[0051] Step 102: input the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model.

[0052] In some embodiments, the preset fault detection model can determine a suitable model according to specific needs, such as a neural network model or a decision tree, etc., and specific equipment can also be used for detection, such as a microcomputer fault recorder, etc. Specifically, the embodiments of the present application do not limit this.

[0053] Step 103, when it is determined that there is fault information in the fault judgment result, the electronic quantity data and the fault information are sent to the dispatching end for storage.

[0054] In some embodiments, before sending the fault information to the dispatching end, the electronic data containing the fault information and the fault information may be packaged and encrypted to ensure the security of the data. After receiving the data, the dispatching end stores it for subsequent analysis and query.

[0055] The fault detection method of the booster station provided by the present disclosure mainly includes the following technical solutions: obtaining the electrical quantity data of the target to be detected; inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model; when it is determined that there is fault information in the fault judgment result, sending the electrical quantity data and the fault information to the dispatching end for storage. Compared with the related art, the embodiment of the present application obtains the electrical quantity data of the target to be detected and inputs it into a preset fault detection model, and performs detection through the preset fault detection model to determine whether a fault occurs in the target to be detected. The efficiency and accuracy of fault detection are improved, and timely response is ensured when a fault occurs. At the same time, the electronic quantity data containing the fault information is sent to the dispatching end for storage, which is helpful for subsequent fault analysis and processing.

[0056] In some embodiments, a protection and fault information remote transmission system substation can be configured at the booster station. The protection and fault information remote transmission system substation should use an embedded real-time operating system to collect and organize various status information of all protection devices and recorders, and transmit it to the dispatching end as needed. The protection and fault information remote transmission system substation communicates with each protection device in the station through a communication interface, adopts standard protocols, accesses the power dispatching data network through an Ethernet interface, and transmits information to the dispatching end.

[0057] In some embodiments, after the fault judgment result is output in step 102, two situations may occur; after no fault information is generated, the following steps are also included:

[0058] When it is determined in the fault judgment result that there is no fault information, the target to be detected is re-detected according to a preset time threshold based on the preset fault detection model.

[0059] In some embodiments, the preset time threshold is an empirical value, which can be determined based on historical data, system characteristics, etc. Specifically, the embodiments of the present application are not limited to this.

[0060] In practical applications, the model needs to be updated and optimized in a timely manner according to the update of the equipment to be tested and the discovery of new failure modes or abnormal conditions.

[0061] Optionally, before inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model, the method further includes:

[0062] Step 201, obtaining training electrical consumption data of a target to be detected; wherein the training electrical consumption data includes abnormal data and normal data.

[0063] In some embodiments, the corresponding various analog quantities and switch quantities can be recorded for training the preset fault detection model, and the electrical quantity data under different working conditions can be collected, covering the changes in electrical quantities of the power system under different operating conditions, including key indicators such as current, voltage, and power factor. At the same time, we also need to ensure that the data contains both electrical quantity data during normal operation and abnormal data when a fault occurs, so as to learn the characteristics of normal data and fault data in the subsequent model training process.

[0064] Before training, you can also set a clear type label for each training electricity consumption data, such as normal or abnormal, to facilitate subsequent model training.

[0065] It should be noted that the training electrical quantity data includes operating electrical quantity data and switching electrical quantity data.

[0066] Step 202: train the preset fault detection model according to the training electrical consumption data, and stop training when the loss function of the preset fault detection model is less than or equal to a preset threshold, to obtain a trained preset fault detection model.

[0067] In some embodiments, in each iteration of training, the preset fault detection model calculates the prediction result based on the current parameters and input data, calculates the value of the loss function, and uses the gradient descent method or other optimization algorithms to update the parameters to reduce the value of the loss function. Repeat the above process until the preset number of iterations is reached or the loss function value is less than the preset threshold; the preset threshold is an empirical value, which can be set according to the accuracy requirements or computer performance, and the embodiments of the present application do not limit this.

[0068] In some embodiments, when it is determined in step 103 that there is fault information in the fault judgment result, when the electronic quantity data and the fault information are sent to the dispatching end for storage, the following steps are also included:

[0069] The fault information is broadcast according to the preset alarm mode.

[0070] In some embodiments, in order to meet the alarm requirements in different scenarios, we can set up multiple alarm methods. For example, in the power system control room, the on-duty personnel can be reminded by sound and light alarms; for the remote monitoring center, relevant personnel can be notified by SMS or email; for important customers or equipment managers, real-time alarm information can also be pushed through mobile phone APP.

[0071] Specifically, the equipment and the maintenance personnel may be bound in advance. When a fault occurs, the maintenance personnel is determined based on the faulty equipment, and a fault alarm is pushed to the maintenance personnel.

[0072] Corresponding to the above-mentioned booster station fault detection method, the present invention also provides a booster station fault detection device. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, the details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0073] Figure 3 A schematic diagram of a fault detection device for a booster station provided in an embodiment of the present disclosure is shown in FIG. Figure 3 As shown, including:

[0074] A first acquisition unit 31 is used to acquire electrical quantity data of a target to be detected;

[0075] A judgment unit 32, used for inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model;

[0076] The sending unit 33 is used to send the electronic quantity data and the fault information to the dispatching end for storage when it is determined that there is fault information in the fault judgment result.

[0077] The fault detection device of the booster station provided by the present disclosure has the following main technical solutions: obtaining the electrical quantity data of the target to be detected; inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model; when it is determined that there is fault information in the fault judgment result, sending the electrical quantity data and the fault information to the dispatching end for storage. Compared with the related art, the embodiment of the present application obtains the electrical quantity data of the target to be detected and inputs it into a preset fault detection model, and performs detection through the preset fault detection model to determine whether a fault occurs in the target to be detected. The efficiency and accuracy of fault detection are improved, and timely response is ensured when a fault occurs. At the same time, the electronic quantity data containing the fault information is sent to the dispatching end for storage, which is helpful for subsequent fault analysis and processing.

[0078] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4 As shown, the device also includes:

[0079] The detection unit 34 is used to re-detect the target to be detected based on the preset fault detection model according to the preset time threshold after the judgment unit 32 inputs the electrical quantity data into the preset fault detection model to obtain the fault judgment result output by the preset fault detection model, if it is determined that there is no fault information in the fault judgment result.

[0080] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4 As shown, the device also includes:

[0081] The second acquisition unit 35 is used to acquire the training electrical quantity data of the target to be detected before the judgment unit 32 inputs the electrical quantity data into the preset fault detection model to obtain the fault judgment result output by the preset fault detection model; wherein the training electrical quantity data includes abnormal data and normal data;

[0082] The training unit 36 ​​is used to train the preset fault detection model according to the training electrical quantity data, and stop the training when the loss function of the preset fault detection model is less than or equal to a preset threshold, so as to obtain a trained preset fault detection model.

[0083] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4As shown, the training electrical quantity data includes operating electrical quantity data and switching electrical quantity data.

[0084] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4 As shown, the sending unit 33 is also used for:

[0085] The fault information is broadcast according to the preset alarm mode.

[0086] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principle is the same, which is no longer limited in the embodiment of the present disclosure.

[0087] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0088] Figure 5 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0089] like Figure 5 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 402 or a computer program loaded from a storage unit 408 to a RAM (Random Access Memory) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An I / O (Input / Output) interface 405 is also connected to the bus 404.

[0090] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0091] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as a fault detection method for a booster station. For example, in some embodiments, the fault detection method for a booster station may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute the aforementioned fault detection method for the booster station in any other appropriate manner (for example, by means of firmware).

[0092] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0093] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0094] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0095] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0096] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0097] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0098] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0099] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0100] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A fault detection method for a booster station, characterized in that: include: Acquire electrical quantity data of the target to be detected; Inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model; When it is determined that fault information exists in the fault judgment result, the electronic quantity data and the fault information are sent to the dispatching end for storage.

2. The method according to claim 1, characterized in that After inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model, the method further includes: When it is determined in the fault judgment result that there is no fault information, the target to be detected is re-detected according to a preset time threshold based on the preset fault detection model.

3. The method according to claim 1, characterized in that Before inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model, the method further includes: Acquire training electrical quantity data of the target to be detected; wherein the training electrical quantity data includes abnormal data and normal data; The preset fault detection model is trained according to the training electrical consumption data, and when the loss function of the preset fault detection model is less than or equal to a preset threshold, the training is stopped to obtain a trained preset fault detection model.

4. The method according to claim 1, characterized in that: The training electrical quantity data includes operation electrical quantity data and switch electrical quantity data.

5. The method according to any one of claims 1 to 4, characterized in that When it is determined that there is fault information in the fault judgment result, sending the electronic quantity data and the fault information to the dispatching end for storage further includes: The fault information is broadcast according to the preset alarm mode.

6. A fault detection device for a booster station, characterized in that: include: A first acquisition unit, used to acquire electrical quantity data of a target to be detected; A judgment unit, used for inputting the electrical quantity data into a preset fault detection model to obtain a fault judgment result output by the preset fault detection model; A sending unit is used to send the electronic quantity data and the fault information to the dispatching end for storage when it is determined that there is fault information in the fault judgment result.

7. The device according to claim 6, characterized in that The device also includes: The detection unit is used to re-detect the target to be detected based on the preset fault detection model according to the preset time threshold after the judgment unit inputs the electrical quantity data into the preset fault detection model to obtain the fault judgment result output by the preset fault detection model, and if it is determined that there is no fault information in the fault judgment result.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 5.

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