A substation intelligent fault early warning system and method based on machine vision

Abstract

The present invention discloses a substation intelligent fault early warning system and method based on machine vision, belonging to the technical field of data processing methods specially suitable for prediction purposes. The present invention collects operation data of substation equipment within a set period and rainfall data of the area where the substation is located, calculates the substation aging value according to the substation aging value calculation strategy, calculates the rainfall abnormal value according to the rainfall abnormal value calculation strategy, calculates the substation fault value according to the substation fault value calculation strategy and compares it with a pre-set substation fault threshold, and issues an early warning to the substation according to the comparison result. By monitoring the operation status of the substation, the risk of equipment damage and accidents is reduced, the stable operation of the substation is guaranteed, and the accuracy and efficiency of fault detection are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing methods specially suitable for prediction purposes, and specifically is a machine vision-based transformer substation intelligent fault early warning system and method. Background Art

[0002] A substation is a place in the power system that transforms voltage and current, receives electric energy and distributes electric energy. Common faults in substations mainly involve insulation failure of equipment, electrical fires, communication control system failures, overvoltage and overcurrent failures, operator errors and other aspects. Substation failures are of many types and various, and require timely repair and maintenance through effective fault diagnosis and troubleshooting methods to ensure the stable operation of the power system and the safety of equipment.

[0003] Existing fault warning systems generally make predictions by training models based on historical operating fault data, but lack the ability to predict special situations. For example, in extreme weather conditions (such as heavy rain and acid rain), the system combines substation equipment operating data to warn of substation faults. For example, a Chinese patent with authorization announcement number CN109586239B discloses a smart substation diagnosis and fault warning method, which includes the following steps: S1: inputting the electrical equipment operating data, network traffic data, and server log data when the substation fault occurs into a database to form fault data, and establishing a large number of data set sample training spaces; S2: capturing network packets through a network packet analysis tool, and uploading the data in the network packets to a database for analysis and display, where the data in the network packets are network data; S3: performing machine learning on the data in the database, and classifying and comparing the fault data and network data through machine learning to obtain a fault model; S4: based on the aforementioned fault model, forming a substation equipment operating fault parameter fluctuation threshold, and accessing the substation data. When the data fluctuation threshold exceeds the warning value of the fault model, a fault warning display is performed.

[0004] In order to solve the above problems, the present invention designs a substation intelligent fault early warning system and method based on machine vision. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention proposes a substation intelligent fault early warning system and method based on machine vision. The present invention collects the operating data of the substation equipment within a set period and the rainfall data of the substation area, calculates the substation aging value according to the substation aging value calculation strategy, calculates the rainfall abnormal value according to the rainfall abnormal value calculation strategy, calculates the substation fault value according to the substation fault value calculation strategy and compares it with the pre-set substation fault threshold, issues an early warning to the substation based on the comparison result, and monitors the operating status of the substation in combination with the rainfall environment. It can predict and alarm in time before potential faults occur, ensure the stable operation of the substation, and improve the accuracy and automation of fault early warning.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A substation intelligent fault early warning method based on machine vision includes the following specific steps:

[0008] Step S1, collecting the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located;

[0009] Step S2, obtaining rainfall data within a set period in the area where the substation is located and substituting it into the rainfall abnormal value calculation strategy to calculate the rainfall abnormal value;

[0010] Step S3, obtaining the operation data of the substation equipment within a set period and substituting it into the substation aging value calculation strategy to calculate the substation aging value;

[0011] Step S4: Substitute the calculated substation aging value and rainfall anomaly value into the substation fault value calculation strategy to calculate the substation fault value and compare it with the preset substation fault threshold, and issue an early warning to the substation according to the comparison result.

[0012] Preferably, the collecting of the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located comprises the following specific steps:

[0013] S11, collecting substation equipment operation data, wherein the substation equipment operation data includes temperature, operation time, vibration frequency and vibration amplitude;

[0014] The temperature is collected by an infrared thermal imaging instrument, and the collected thermal imaging image is imported into the image processing module to obtain temperature data exceeding the preset maximum safe temperature threshold and stored in the temperature data storage module;

[0015] The running time is collected by a timer, and the collected running time is stored in a running time storage module;

[0016] The vibration frequency and vibration amplitude are collected by a vibration sensor, and the collected vibration frequency and vibration amplitude data are imported into a vibration processing module to obtain vibration frequency data exceeding a preset maximum safe vibration frequency threshold and vibration amplitude data exceeding a preset maximum safe vibration amplitude threshold and store them in a vibration data storage module;

[0017] S12, collecting rainfall data within a set period in the area where the substation is located, wherein the rainfall data in the area where the substation is located includes rainfall and pH value, wherein the rainfall is collected by a rain gauge, and the pH value is collected by a pH meter, and the collected rainfall is introduced into a rainfall data processing module to obtain rainfall data exceeding a preset maximum safe rainfall threshold, and the collected pH value is introduced into a pH value analysis module to screen out pH value data indicating that the rainfall is acidic rainfall, and the rainfall data and pH value data are stored in a rainfall data storage module;

[0018] Preferably, the step of obtaining rainfall data within a set period in the area where the substation is located and substituting the data into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value comprises the following specific steps:

[0019] S21, obtaining rainfall data within a set period in the area where the substation is located, including rainfall and pH value in the rainfall data storage module;

[0020] S22, substituting the acquired rainfall data within a set period of the area where the substation is located into a rainfall anomaly value calculation strategy to calculate a rainfall anomaly value, wherein the rainfall anomaly value calculation strategy includes a rainfall anomaly value calculation formula, and the rainfall anomaly value calculation formula is:

[0021] ,

[0022] in, For the collection of The amount of rainfall during a period of time, is the maximum discharge threshold, is the number of time periods for collecting rainfall, For the collection of The pH value of rainfall in a period of time, , The value is 0, is e raised to a power.

[0023] Preferably, the step of obtaining the operation data of the substation equipment within a set period and substituting it into the substation aging value calculation strategy to calculate the substation aging value comprises the following specific steps:

[0024] S31, obtaining the operation data of the substation equipment within a set period, including the temperature data in the temperature data storage module, the operation time data, and the vibration frequency and vibration amplitude data in the vibration data storage module;

[0025] S32, substituting the obtained operation data of the substation equipment within the set period into the substation aging value calculation strategy to calculate the substation aging value, wherein the substation aging value calculation strategy includes a substation aging value calculation formula, and the substation aging value calculation formula is:

[0026] ,

[0027] in, For the collection of The temperature during a period of time, is the maximum safe temperature threshold, is the number of time periods for collecting temperature, The operating time of the substation to be monitored, For the service life of the substation, For the collection of The vibration frequency within a period of time, is the maximum safe vibration frequency threshold, is the number of time periods of the collected vibration frequency, For the collection of The vibration amplitude within a time period, is the maximum safe vibration amplitude threshold, is the number of time periods of the collected vibration amplitude, is the temperature ratio, is the running time ratio, is the vibration ratio, is the coefficient of vibration frequency in vibration influence, is the coefficient of vibration amplitude in vibration influence, are all positive numbers, .

[0028] Preferably, the step of substituting the calculated substation aging value and rainfall anomaly value into the substation fault value calculation strategy to calculate the substation fault value and comparing it with a preset substation fault threshold, and issuing an early warning to the substation according to the comparison result comprises the following specific steps:

[0029] S41, substituting the calculated substation aging value and rainfall abnormality value into the substation fault value calculation strategy to calculate the substation fault value, wherein the substation fault value calculation strategy includes a substation fault value calculation formula, and the substation fault value calculation formula is:

[0030] ,

[0031] in, is the aging ratio, is the rainfall proportion coefficient, and are all positive numbers, ;

[0032] S42: Compare the calculated substation fault value with a preset substation fault threshold. If the substation fault value is greater than or equal to the preset substation fault threshold, issue an early warning to the substation.

[0033] Above The method for obtaining the value of the substation fault threshold is as follows: select 2000 substations with faults, obtain the operating data of the substation equipment within the set period and the rainfall data of the area where the substation is located, substitute them into the substation aging value calculation formula and the rainfall abnormal value calculation formula to calculate the substation aging value and rainfall abnormal value respectively, and substitute them into the substation fault value calculation formula to calculate the substation fault value, select industry experts to calculate the fault values ​​of these 2000 substations with faults, and import the calculated fault values ​​together with the substation fault values ​​calculated by the substation fault value calculation formula into the relevant fitting software to output a set of the highest accuracy and the value of the substation fault threshold.

[0034] A substation intelligent fault early warning system based on machine vision, which is implemented based on the above-mentioned substation intelligent fault early warning method based on machine vision, including a data acquisition module, a data storage module, an image acquisition module, an image processing module, an aging calculation module, a rainfall anomaly calculation module, a fault calculation module, a fault early warning module and a control module;

[0035] Preferably, the data acquisition module is used to collect the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located;

[0036] The data storage module is used to store the collected substation equipment operation data and rainfall data in the area where the substation is located;

[0037] The image acquisition module is used to collect thermal images taken by infrared thermal imaging instruments;

[0038] The image processing module is used to process the collected thermal images;

[0039] The aging calculation module is used to obtain the operation data of the substation equipment within the set period and substitute it into the substation aging value calculation strategy to calculate the substation aging value;

[0040] The rainfall anomaly calculation module is used to obtain the rainfall data within a set period in the area where the substation is located and substitute it into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value;

[0041] The fault calculation module is used to substitute the calculated substation aging value and rainfall abnormal value into the substation fault value calculation strategy to calculate the substation fault value;

[0042] The fault warning module is used to compare the calculated substation fault value with the pre-set substation fault threshold, and issue a warning to the substation based on the comparison result;

[0043] The control module is used to control the operation of the data acquisition module, the data storage module, the image acquisition module, the image processing module, the aging calculation module, the rainfall anomaly calculation module, the fault calculation module and the fault warning module.

[0044] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-mentioned intelligent fault warning method for substation based on machine vision by calling the computer program stored in the memory.

[0045] A computer-readable storage medium stores instructions. When the instructions are executed on a computer, the computer executes the above-mentioned intelligent fault early warning method for a substation based on machine vision.

[0046] The beneficial effects of the present invention are as follows: the present invention collects the operation data of the substation equipment within the set period and the rainfall data of the area where the substation is located, calculates the substation aging value according to the substation aging value calculation strategy, calculates the rainfall abnormal value according to the rainfall abnormal value calculation strategy, calculates the substation fault value according to the substation fault value calculation strategy and compares it with the pre-set substation fault threshold, and issues an early warning to the substation according to the comparison result;

[0047] By combining rainfall environment monitoring with substation operation status, potential faults can be predicted and timely alarmed before they occur, thus reducing the risk of equipment damage and accidents and ensuring the stable operation of the substation;

[0048] The intelligent fault warning system for substations based on machine vision can reduce reliance on manual inspections and improve the accuracy and efficiency of fault warnings through automated monitoring methods. Timely fault warnings can shorten fault handling time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative labor, among which:

[0050] Figure 1 A schematic diagram of a process flow of a substation intelligent fault early warning method based on machine vision according to the present invention;

[0051] Figure 2 The figure is a schematic diagram of the overall framework of a substation intelligent fault warning system based on machine vision according to the present invention. DETAILED DESCRIPTION

[0052] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0053] Example 1

[0054] See also Figure 1 , an embodiment provided by the present invention: a substation intelligent fault early warning method based on machine vision, which comprises the following specific steps:

[0055] Step S1, collecting the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located;

[0056] In this embodiment, collecting the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located includes the following specific steps:

[0057] S11. Collect substation equipment operation data, which includes temperature, operation time, vibration frequency and vibration amplitude.

[0058] Specifically, the temperature can be collected by an infrared thermal imaging instrument, and the collected thermal imaging image is imported into the image processing module to obtain temperature data exceeding a preset maximum safe temperature threshold and stored in the temperature data storage module.

[0059] The specific steps of infrared thermal imaging instrument and image processing module to process images are as follows:

[0060] Aim the infrared thermal imaging instrument at the area where the substation equipment is located, adjust the lens and focal length until the substation equipment can be clearly monitored, start the infrared thermal imaging instrument, collect thermal images of the target area, and the image shows the color difference of different temperature areas, where red represents high temperature and blue represents low temperature. Import the collected thermal images into a dedicated image processing module, and set a maximum safe temperature threshold in the image processing module. This threshold can be set according to actual needs and industry standards. Generally speaking, the transformer oil temperature should be between 60℃ and 90℃, the high-voltage switch room temperature should be between 20℃ and 40℃, and the low-voltage equipment room temperature should be between 5℃ and 35℃. Exceeding these ranges will have an adverse effect on the safety, reliability and life of the equipment. The image processing module analyzes the thermal image, identifies the area that exceeds the preset maximum safe temperature threshold, and stores the acquired data that exceeds the safe temperature threshold in the temperature data storage module. These data are used for monitoring, historical backtracking, alarm notification and other purposes.

[0061] The operating time is collected by a timer, and the collected operating time is stored in a operating time storage module. The specific steps for collecting the operating time by a timer are: installing a timer in the substation equipment, detecting the start and stop time of the substation equipment, and the time period of continuous operation of the equipment, and extracting the total operating time of the substation equipment.

[0062] The vibration frequency and vibration amplitude are collected by the vibration sensor, and the collected vibration frequency and vibration amplitude data are imported into the vibration processing module to obtain the vibration frequency data exceeding the preset maximum safe vibration frequency threshold and the vibration amplitude data exceeding the preset maximum safe vibration amplitude threshold and store them in the vibration data storage module.

[0063] The specific steps for collecting vibration frequency and vibration amplitude through vibration sensors are as follows:

[0064] The installation location of the sensor is usually selected at the key parts of the equipment, such as bearings, gears, blades, etc. The vibration sensor is connected to the data acquisition equipment (such as data acquisition module, sensor controller, etc.). According to the vibration characteristics of the substation equipment, a suitable sampling frequency is set. The sampling frequency should be more than twice the highest frequency of the equipment vibration signal to ensure complete monitoring of the signal. The maximum safe vibration frequency threshold and the maximum safe vibration amplitude threshold are pre-set according to the actual historical safe operation conditions. For example, the frequency range of the transformer vibration during operation is 10Hz~1000Hz, and the vibration amplitude is less than 20mm / s, which means the operation is normal. The collected vibration frequency and vibration amplitude are imported into the vibration processing module to obtain the vibration frequency data exceeding the preset maximum safe vibration frequency threshold and the vibration amplitude data exceeding the preset maximum safe vibration amplitude threshold and store them in the vibration data storage module.

[0065] S12. Collect rainfall data within a set period in the area where the substation is located. The rainfall data in the area where the substation is located includes rainfall and pH value. The rainfall is collected by a rain gauge and the pH value is collected by a pH meter. The collected rainfall is imported into a rainfall data processing module to obtain rainfall data exceeding a preset maximum safe rainfall threshold. The collected pH value is imported into a pH value analysis module to filter out pH value data of acidic rainfall. The rainfall data and pH value data are stored in a rainfall data storage module. Monitoring the rainfall and pH value of rainwater in the substation is to evaluate the impact of the environment on the substation equipment, especially the potential threat of acidic rainfall to equipment corrosion.

[0066] The specific steps for collecting rainfall data within a set period in the area where the substation is located are:

[0067] A rain gauge is installed near the substation. The installation location can represent the impact of rainfall on the substation. The maximum safe rainfall threshold is set according to the rainfall range that can be tolerated in the substation production standard. The collected rainfall is imported into the rainfall data processing module to obtain rainfall data that exceeds the preset maximum safe rainfall threshold. The pH value of the rainfall is measured by a pH meter. When the pH value of rainwater is less than 5.6, it is usually called acidic rainfall. This is because acidic gases such as sulfur dioxide in the atmosphere are dissolved in the rainwater, showing obvious acidity. When the pH value of precipitation is greater than or equal to 4.5 and less than 5.6, it is weak acid rain. When the pH value of precipitation is less than 4.5, it is strong acid rain. The collected pH value is imported into the pH value analysis module to screen out the pH value data of acidic rainfall, and the rainfall data and pH value data are stored in the rainfall data storage module.

[0068] Step S2: Obtain rainfall data within a set period in the area where the substation is located and substitute it into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value.

[0069] In this embodiment, obtaining rainfall data within a set period in the area where the substation is located and substituting it into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value includes the following specific steps:

[0070] S21, obtaining rainfall data within a set period in the area where the substation is located, including rainfall and pH value in the rainfall data storage module;

[0071] S22, substituting the acquired rainfall data within the set period of the substation area into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value, the rainfall anomaly value calculation strategy includes a rainfall anomaly value calculation formula, and the rainfall anomaly value calculation formula is:

[0072] ,

[0073] in, For the collection of The amount of rainfall during a period of time, is the maximum discharge threshold, is the number of time periods for collecting rainfall, For the collection of The pH value of rainfall in a period of time, , The value is 0, is e raised to a power.

[0074] Step S3: Obtain the operation data of the substation equipment within a set period and substitute it into the substation aging value calculation strategy to calculate the substation aging value.

[0075] In this embodiment, obtaining the operation data of the substation equipment within a set period and substituting it into the substation aging value calculation strategy to calculate the substation aging value includes the following specific steps:

[0076] S31, obtaining the operation data of the substation equipment within a set period, including the temperature data in the temperature data storage module, the operation time data, and the vibration frequency and vibration amplitude data in the vibration data storage module;

[0077] S32, substituting the obtained operation data of the substation equipment within the set period into the substation aging value calculation strategy to calculate the substation aging value, wherein the substation aging value calculation strategy includes a substation aging value calculation formula, and the substation aging value calculation formula is:

[0078] ,

[0079] in, For the collection of The temperature during a period of time, is the maximum safe temperature threshold, is the number of time periods for collecting temperature, The operating time of the substation to be monitored, For the service life of the substation, For the collection of The vibration frequency within a period of time, is the maximum safe vibration frequency threshold, is the number of time periods of the collected vibration frequency, For the collection of The vibration amplitude within a time period, is the maximum safe vibration amplitude threshold, is the number of time periods of the collected vibration amplitude, is the temperature ratio, is the running time ratio, is the vibration ratio, is the coefficient of vibration frequency in vibration influence, is the coefficient of vibration amplitude in vibration influence, are all positive numbers, .

[0080] Step S4: Substitute the calculated substation aging value and rainfall anomaly value into the substation fault value calculation strategy to calculate the substation fault value and compare it with the preset substation fault threshold, and issue an early warning to the substation according to the comparison result.

[0081] In this embodiment, the calculated substation aging value and rainfall anomaly value are substituted into the substation fault value calculation strategy to calculate the substation fault value and compare it with the pre-set substation fault threshold. The substation is warned according to the comparison result, including the following specific steps:

[0082] S41, substituting the calculated substation aging value and rainfall abnormality value into the substation fault value calculation strategy to calculate the substation fault value, wherein the substation fault value calculation strategy includes a substation fault value calculation formula, and the substation fault value calculation formula is:

[0083] ,

[0084] in, is the aging ratio, is the rainfall proportion coefficient, and are all positive numbers, ;

[0085] S42: Compare the calculated substation fault value with a preset substation fault threshold. If the substation fault value is greater than or equal to the preset substation fault threshold, issue an early warning to the substation.

[0086] Above The method for obtaining the value of the substation fault threshold is as follows: select 2000 substations with faults, obtain the operating data of the substation equipment within the set period and the rainfall data of the area where the substation is located, substitute them into the substation aging value calculation formula and the rainfall abnormal value calculation formula to calculate the substation aging value and rainfall abnormal value respectively, and substitute them into the substation fault value calculation formula to calculate the substation fault value, select industry experts to calculate the fault values ​​of these 2000 substations with faults, and import the calculated fault values ​​together with the substation fault values ​​calculated by the substation fault value calculation formula into the relevant fitting software to output a set of the highest accuracy and the value of the substation fault threshold.

[0087] Example 2

[0088] See also Figure 2, a substation intelligent fault early warning system based on machine vision, which is implemented based on the above-mentioned substation intelligent fault early warning method based on machine vision, including a data acquisition module, a data storage module, an image acquisition module, an image processing module, an aging calculation module, a rainfall anomaly calculation module, a fault calculation module, a fault early warning module and a control module;

[0089] In this embodiment, the data acquisition module is used to collect the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located;

[0090] The data storage module is used to store the collected substation equipment operation data and rainfall data in the area where the substation is located;

[0091] The image acquisition module is used to collect thermal images taken by infrared thermal imaging instruments;

[0092] The image processing module is used to process the collected thermal images;

[0093] The aging calculation module is used to obtain the operation data of the substation equipment within the set period and substitute it into the substation aging value calculation strategy to calculate the substation aging value;

[0094] The rainfall anomaly calculation module is used to obtain the rainfall data within a set period in the area where the substation is located and substitute it into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value;

[0095] The fault calculation module is used to substitute the calculated substation aging value and rainfall abnormal value into the substation fault value calculation strategy to calculate the substation fault value;

[0096] The fault warning module is used to compare the calculated substation fault value with the pre-set substation fault threshold, and issue a warning to the substation based on the comparison result;

[0097] The control module is used to control the operation of the data acquisition module, the data storage module, the image acquisition module, the image processing module, the aging calculation module, the rainfall anomaly calculation module, the fault calculation module and the fault warning module.

[0098] Example 3

[0099] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes the above-mentioned substation intelligent fault warning method based on machine vision by calling the computer program stored in the memory.

[0100] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a machine vision-based substation intelligent fault warning method provided in the above method embodiment. The electronic device may also include other components for realizing the functions of the device. For example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data, which will not be described in detail in this embodiment.

[0101] Example 4

[0102] This embodiment provides a computer-readable storage medium storing instructions, which, when a computer program is executed on a computer device, enables the computer device to execute the above-mentioned intelligent fault early warning method for a substation based on machine vision.

[0103] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0104] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A substation intelligent fault early warning method based on machine vision, characterized in that: It includes the following specific steps: Step S1, collecting the operation data of the substation equipment within a set period and the rainfall data of the area where the substation is located; Step S2, obtaining rainfall data within a set period in the area where the substation is located and substituting it into the rainfall abnormal value calculation strategy to calculate the rainfall abnormal value; Step S3, obtaining the operation data of the substation equipment within a set period and substituting it into the substation aging value calculation strategy to calculate the substation aging value; Step S4, substituting the calculated substation aging value and rainfall abnormal value into the substation fault value calculation strategy to calculate the substation fault value and comparing it with the pre-set substation fault threshold, and issuing an early warning to the substation according to the comparison result; The step S2 comprises the following specific steps: S21, obtaining rainfall data within a set period in the area where the substation is located, including rainfall and pH value in the rainfall data storage module; S22, substituting the acquired rainfall data within a set period of the area where the substation is located into a rainfall anomaly value calculation strategy to calculate a rainfall anomaly value, wherein the rainfall anomaly value calculation strategy includes a rainfall anomaly value calculation formula, and the rainfall anomaly value calculation formula is: ， in, For the collection of The amount of rainfall during a period of time, is the maximum discharge threshold, is the number of time periods for collecting rainfall, For the collection of The pH value of rainfall in a period of time, , The value is 0, is the power of e; The step S3 comprises the following specific steps: S31, obtaining the operation data of the substation equipment within a set period, including the temperature data in the temperature data storage module, the operation time data, and the vibration frequency and vibration amplitude data in the vibration data storage module; S32, substituting the obtained operation data of the substation equipment within the set period into the substation aging value calculation strategy to calculate the substation aging value, wherein the substation aging value calculation strategy includes a substation aging value calculation formula, and the substation aging value calculation formula is: ， in, For the collection of The temperature during a period of time, is the maximum safe temperature threshold, is the number of time periods for collecting temperature, The operating time of the substation to be monitored, For the service life of the substation, For the collection of The vibration frequency within a period of time, is the maximum safe vibration frequency threshold, is the number of time periods of the collected vibration frequency, For the collection of The vibration amplitude within a time period, is the maximum safe vibration amplitude threshold, is the number of time periods of the collected vibration amplitude, is the temperature ratio, is the running time ratio, is the vibration ratio, is the coefficient of vibration frequency in vibration influence, is the coefficient of vibration amplitude in vibration influence, are all positive numbers, ; The step S4 comprises the following specific steps: S41, substituting the calculated substation aging value and rainfall abnormality value into the substation fault value calculation strategy to calculate the substation fault value, wherein the substation fault value calculation strategy includes a substation fault value calculation formula, and the substation fault value calculation formula is: ， in, is the aging ratio, is the rainfall proportion coefficient, and are all positive numbers, ; S42: Compare the calculated substation fault value with a preset substation fault threshold. If the substation fault value is greater than or equal to the preset substation fault threshold, issue an early warning to the substation.

2. A method for intelligent fault early warning of a substation based on machine vision as claimed in claim 1, characterized in that: The step S1 comprises the following specific steps: S11, collecting operation data of substation equipment within a set period, wherein the operation data of substation equipment includes temperature, operation time, vibration frequency and vibration amplitude; S12, collecting rainfall data within a set period in the area where the substation is located, wherein the rainfall data in the area where the substation is located includes rainfall amount and pH value.

3. A substation intelligent fault early warning system based on machine vision, which is implemented based on the substation intelligent fault early warning method based on machine vision as claimed in any one of claims 1-2, characterized in that: It includes a data acquisition module, a data storage module, an image acquisition module, an image processing module, an aging calculation module, a rainfall anomaly calculation module, a fault calculation module, a fault warning module and a control module; The data acquisition module is used to collect the operating data of the substation equipment within the set period and the rainfall data of the area where the substation is located; The data storage module is used to store the collected substation equipment operation data and rainfall data in the area where the substation is located; The image acquisition module is used to collect thermal images; The image processing module is used to process the collected thermal images; The aging calculation module is used to obtain the operation data of the substation equipment within the set period and substitute it into the substation aging value calculation strategy to calculate the substation aging value; The rainfall anomaly calculation module is used to obtain the rainfall data within a set period in the area where the substation is located and substitute it into the rainfall anomaly value calculation strategy to calculate the rainfall anomaly value; The fault calculation module is used to substitute the calculated substation aging value and rainfall abnormal value into the substation fault value calculation strategy to calculate the substation fault value; The fault warning module is used to compare the calculated substation fault value with the pre-set substation fault threshold, and issue a warning to the substation based on the comparison result; The control module is used to control the operation of the data acquisition module, the data storage module, the image acquisition module, the image processing module, the aging calculation module, the rainfall anomaly calculation module, the fault calculation module and the fault warning module.

4. An electronic device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program that can be called by the processor, and the processor executes the machine vision-based substation intelligent fault warning method described in any one of claims 1-2 by calling the computer program stored in the memory.

5. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes a substation intelligent fault warning method based on machine vision as described in any one of claims 1-2.

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