Transformer substation fire monitoring method, monitoring device, program product and monitoring system

Abstract

The invention provides a transformer substation fire monitoring method, a monitoring device, a program product and a monitoring system. The method comprises the following steps: acquiring multiple groups of target sensor data through sensor equipment; determining whether a target to-be-detected line exists according to the multiple groups of target sensor data; under the condition that the target to-be-detected line exists, obtaining a target infrared image through target infrared equipment; and according to the target infrared image, determining whether the target to-be-detected line has a fire or not at the second target time node. According to the method, the problem of poor timeliness of a transformer substation fire monitoring method in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of substation fire monitoring, and in particular to a substation fire monitoring method, a substation fire monitoring device, a computer program product and a substation fire monitoring system. Background Art

[0002] Substations are key facilities in the power system, and their safe operation is crucial to the reliability of power supply. However, oil-immersed transformers, as core components of substations, are at risk of fire, which may cause equipment damage and power outages. The main cause of fire is local overheating inside the transformer, which generates arcs and ignites the insulating oil. In order to detect and respond to this potential threat as early as possible, substations need reliable fire detection systems.

[0003] In the early stages of a fire, smoke is often produced first. If the smoke can be detected accurately, the danger can be controlled in the early stages. The traditional sensor-based smoke detection method is easily affected by the environment, has a certain alarm delay and is not suitable for large-scale environments such as outdoor. With the rapid development of intelligent video technology, research on smoke detection using video recognition technology has begun. In the current field of substation fire detection, it is usually necessary to obtain a video of the substation line, and then determine whether a fire has occurred in the line based on the line video. However, video recognition occupies more network bandwidth resources, and the background server load is heavy when multiple data are transmitted and detected in real time at the same time, and the timeliness is relatively poor.

[0004] Currently, there is no solution to the above problem. Summary of the invention

[0005] The main purpose of the present application is to provide a substation fire monitoring method, a substation fire monitoring device, a computer program product and a substation fire monitoring system, so as to at least solve the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a substation fire monitoring method is provided, the substation includes multiple lines to be tested, each of the lines to be tested is installed with a sensor device, an infrared device is installed directly above each of the lines to be tested, each of the sensor devices and each of the infrared devices are communicatively connected to a background server, the method is applied to the background server, the method includes: obtaining multiple groups of target sensor data through the sensor device, the target sensor data is the sensor data of the line to be tested under a first target time node, the first target time node is any sensor time node, the sensor time node is the time node of the sensor device, the sensor data includes: the temperature of the line to be tested, the The target sensor data comprises the following: a current of the circuit to be tested, a voltage of the circuit to be tested, and a residual current of the circuit to be tested; determining whether there is a target circuit to be tested according to the multiple groups of target sensor data, the target circuit to be tested being the circuit to be tested that has a risk of fire at a second target time node, and the second target time node being the sensor time node next to the first target time node; in the case where the target circuit to be tested exists, acquiring a target infrared image through a target infrared device, the target infrared device being the infrared device on the target circuit to be tested, and the target infrared image being the infrared image of the target circuit to be tested at the second target time node; determining whether a fire occurs in the target circuit to be tested at the second target time node according to the target infrared image.

[0007] Optionally, in the process of determining whether there is a target line to be tested according to the multiple groups of target sensor data, the method includes: inputting each group of the target sensor data into a temperature prediction model to obtain multiple target temperatures, one target temperature corresponds to one line to be tested, and one target temperature is the temperature of the corresponding line to be tested at the second target time node, and the temperature prediction model is obtained by training a neural network using multiple groups of first training data, wherein each group of the first training data includes: the sensor data of one line to be tested at one sensor time node, and the temperature of the line to be tested at the sensor time node next to the sensor time node; when the target temperature is greater than a predetermined temperature, determining that the line to be tested corresponding to the target temperature is the target line to be tested.

[0008] Optionally, before acquiring the target infrared image through the target infrared device, the method includes: acquiring a third target time node and a fourth target time node through the target sensor device, the target sensor device is the sensor device on the target line to be tested, the third target time node is the sensor time node next to the second target time node, the fourth target time node is the server time node when the background server acquires the third target time node, and the server time node is the time node of the background server; calculating the difference between the third target time node and the fourth target time node to obtain a first time difference; calculating the difference between the second target time node and the first time node The fifth target time node is obtained by calculating the difference between the difference between the fifth target time node and the second time difference; the sixth target time node is obtained through the target infrared device, and the seventh target time node is obtained, the sixth target time node is an infrared time node, the infrared time node is the time node of the target infrared device, and the seventh target time node is the server time node when the background server obtains the sixth target time node; the difference between the sixth target time node and the seventh target time node is calculated to obtain the second time difference; the sum of the fifth target time node and the second time difference is calculated to obtain the sixth target time node; and the infrared image collected by the target infrared device at the sixth target time node is determined to be the target infrared image.

[0009] Optionally, determining whether a fire occurs in the target line to be tested at the second target time node based on the target infrared image includes: dividing the target infrared image into a plurality of square areas of equal size; respectively calculating the average value of the grayscale values ​​of the pixels in each of the square areas to obtain a plurality of average grayscale values, wherein the average grayscale values ​​correspond one-to-one to the square areas; and determining that a fire occurs in the target line to be tested at the second target time node when at least one of the average grayscale values ​​is greater than a predetermined grayscale value.

[0010] Optionally, an alarm device is installed on each of the lines to be tested, and each of the alarm devices is communicatively connected to the background server. After determining whether a fire has occurred in the target line to be tested at the second target time node based on the target infrared image, the method further includes: in the event that a fire has occurred in the target line to be tested at the second target time node, controlling the target alarm device to give an audible and visual alarm, the target alarm device being the alarm device on the target line to be tested; sending feedback information to a display device so that the display device displays the feedback information, the feedback information indicating that a fire has occurred in the target line to be tested, and the feedback information including: the number of the substation and the number of the target line to be tested.

[0011] Optionally, after determining whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image, the method further includes: obtaining target meteorological information through the sensor device, the target meteorological information is the meteorological information of the target line to be tested at the second target time node, and the meteorological information includes: wind speed and wind direction; obtaining flammable parameter information of each electrical device on the target line to be tested, and the flammable parameter information includes: ignition temperature, combustion temperature, and spontaneous combustion temperature; inputting the meteorological information of the target line to be tested, the target infrared image, and the flammable parameter information of each electrical device on the target line to be tested into a fire path prediction model to obtain the fire path of the target line to be tested, and the fire path prediction model is obtained by training a neural network with second training data, wherein each group of the second training data at least includes: the meteorological information of the line to be tested, the infrared image of the line to be tested, the flammable parameter information of each electrical device on the line to be tested, and the fire path of the line to be tested, obtained within a historical period, and the fire path is a numbering sequence composed of the numbers of each electrical device arranged in the order of occurrence of the fire.

[0012] Optionally, after acquiring the target infrared image through the target infrared device, the method further comprises: performing image enhancement processing and image noise reduction processing on the target infrared image in sequence.

[0013] According to another aspect of the present application, a substation fire monitoring device is provided. The substation includes multiple lines to be tested, each of the lines to be tested is installed with a sensor device, and an infrared device is installed directly above each of the lines to be tested. Each of the sensor devices and each of the infrared devices are communicatively connected to a background server. The device is applied to the background server, and the device includes: a first acquisition unit, which is used to acquire multiple groups of target sensor data through the sensor device, and the target sensor data is the sensor data of one of the lines to be tested at a first target time node. The first target time node is any sensor time node, and the sensor time node is the time node of the sensor device. The sensor data includes: the temperature of the line to be tested, the current of the line to be tested, and the current of the line to be tested. the voltage of the target line to be tested and the residual current of the target line to be tested; a first determining unit, used to determine whether there is a target line to be tested according to the multiple groups of target sensor data, the target line to be tested is the line to be tested that has a risk of fire at a second target time node, and the second target time node is the next sensor time node of the first target time node; a second acquiring unit, used to acquire a target infrared image through a target infrared device when the target line to be tested exists, the target infrared device is the infrared device on the target line to be tested, and the target infrared image is the infrared image of the target line to be tested at the second target time node; the second determining unit, used to determine whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image.

[0014] According to another aspect of the present application, a computer program product is provided, including a computer program / instruction, and when the computer program / instruction is executed by a processor, any one of the substation fire monitoring methods is implemented.

[0015] According to another aspect of the present application, a substation fire monitoring system is provided, the system comprising: a plurality of sensor devices, the substation comprising a plurality of lines to be tested, one of the sensor devices corresponding to one of the lines to be tested, and the sensor device being installed on the corresponding line to be tested; a plurality of infrared devices, one of the infrared devices corresponding to one of the lines to be tested, and the infrared device being installed directly above the corresponding line to be tested; a plurality of alarm devices, one of the alarm devices corresponding to one of the lines to be tested, and the alarm device being installed on the corresponding line to be tested; a display device; the background server being respectively communicatively connected to each of the sensor devices, and respectively communicatively connected to each of the infrared devices, and respectively communicatively connected to each of the alarm devices, and communicatively connected to the display device, the background server being used to execute any one of the substation fire monitoring methods described.

[0016] By applying the technical solution of the present application, first, the sensor data of the line to be tested at the first target time node is obtained, and then, based on the sensor data, the line to be tested that has a risk of fire at the second target time node, namely, the target line to be tested, is screened out. After that, only the infrared image of the target line to be tested at the second target time node needs to be obtained. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining the video of each line. In addition, the sensor data transmission only needs to occupy less network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a process of a substation fire monitoring method provided according to an embodiment of the present application is shown;

[0018] Figure 2 A structural block diagram of a substation fire monitoring device provided according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0019] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0022] As introduced in the background technology, the substation fire monitoring method in the prior art has poor timeliness. In order to solve the problem of poor timeliness of the substation fire monitoring method in the prior art, the embodiments of the present application provide a substation fire monitoring method, a substation fire monitoring device, a computer program product and a substation fire monitoring system.

[0023] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0024] In this embodiment, a substation fire monitoring system is provided, and the system includes:

[0025] A plurality of sensor devices, the substation includes a plurality of lines to be tested, one of the sensor devices corresponds to one of the lines to be tested, and the sensor device is installed on the corresponding line to be tested;

[0026] Specifically, the sensor equipment includes: a temperature sensor, a current sensor, a voltage sensor and a leakage current sensor. The temperature sensor is used to obtain the temperature of the circuit to be tested, the current sensor is used to obtain the current of the circuit to be tested, the voltage sensor is used to obtain the voltage of the circuit to be tested, and the leakage current sensor is used to obtain the residual current of the circuit to be tested.

[0027] A plurality of infrared devices, one of the infrared devices corresponds to one of the circuits to be tested, and the infrared devices are installed directly above the corresponding circuits to be tested;

[0028] Specifically, the infrared device may be an infrared camera, which is used to collect infrared images of the circuit to be tested.

[0029] A plurality of alarm devices, one of the alarm devices corresponds to one of the lines to be tested, and the alarm devices are installed on the corresponding lines to be tested;

[0030] Display devices;

[0031] The above-mentioned background server is respectively connected in communication with each of the above-mentioned sensor devices, and is respectively connected in communication with each of the above-mentioned infrared devices, and is respectively connected in communication with each of the above-mentioned alarm devices, and is also connected in communication with the above-mentioned display device. The above-mentioned background server is used to execute the above-mentioned substation fire monitoring method.

[0032] Through the above embodiment, first, the sensor data of the line to be tested at the first target time node is obtained through the sensor device, and then, the line to be tested with a fire risk at the second target time node, that is, the target line to be tested, is screened out based on the sensor data. After that, it is only necessary to obtain an infrared image of the target line to be tested at the second target time node through the infrared device. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining the video of each line, and the sensor data transmission only needs to occupy less network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0033] In this embodiment, a substation fire monitoring method running on a background server is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 1 FIG. 1 is a flow chart of a method for monitoring a substation fire according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0035] Step S201, acquiring multiple groups of target sensor data through the above sensor device;

[0036] The target sensor data is sensor data of the line to be tested at the first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested;

[0037] Specifically, the substation includes multiple lines to be tested, each of the above-mentioned lines to be tested is installed with a sensor device, and an infrared device is installed directly above each of the above-mentioned lines to be tested. Each of the above-mentioned sensor devices and each of the above-mentioned infrared devices are communicatively connected to the background server, wherein the sensor devices include: a temperature sensor, a current sensor, a voltage sensor, a leakage current sensor and a wind speed and direction sensor. The temperature sensor is used to obtain the temperature of the line to be tested, the current sensor is used to obtain the current of the line to be tested, the voltage sensor is used to obtain the voltage of the line to be tested, the leakage current sensor is used to obtain the residual current of the line to be tested, and the wind speed and direction sensor is used to obtain the meteorological information of the line to be tested.

[0038] Step S202, determining whether there is a target line to be tested according to the above multiple sets of target sensor data;

[0039] The target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node;

[0040] Specifically, there may be multiple target circuits to be tested.

[0041] In an optional solution, during the above step S202, the above method further includes:

[0042] Input each group of the target sensor data into the temperature prediction model to obtain multiple target temperatures, one target temperature corresponds to one of the lines to be tested, and one target temperature is the temperature of the corresponding line to be tested at the second target time node. The temperature prediction model is obtained by training a neural network using multiple groups of first training data, wherein each group of the first training data includes: the sensor data of one of the lines to be tested at one of the sensor time nodes, and the temperature of the line to be tested at the next sensor time node of the sensor time node;

[0043] Specifically, in some implementations, the first target time node is 11:13, and the second target time node is 11:14. The sensor data of each line to be tested at 11:13 is input into the prediction model to obtain the temperature of each line to be tested at 11:14.

[0044] When the target temperature is greater than a predetermined temperature, the circuit to be tested corresponding to the target temperature is determined as the target circuit to be tested.

[0045] Specifically, when the temperature of the line under test at the second target time node (target temperature) is greater than the predetermined temperature, it is determined that the line under test has a fire risk at the second target time node, that is, the line under test is determined to be the target line under test.

[0046] Step S203, when the target circuit to be tested exists, obtaining a target infrared image through a target infrared device;

[0047] Wherein, the target infrared device is the infrared device on the target circuit to be tested, and the target infrared image is the infrared image of the target circuit to be tested at the second target time node;

[0048] In an optional solution, before the above step S203, the above method further includes:

[0049] Obtain a third target time node and a fourth target time node through a target sensor device, the target sensor device is the sensor device on the target line to be tested, the third target time node is the sensor time node next to the second target time node, the fourth target time node is the server time node when the background server obtains the third target time node, and the server time node is the time node of the background server;

[0050] Calculate the difference between the third target time node and the fourth target time node to obtain a first time difference;

[0051] Calculate the difference between the second target time node and the first time difference to obtain a fifth target time node;

[0052] Obtain a sixth target time node through the target infrared device, and obtain a seventh target time node, the sixth target time node is an infrared time node, the infrared time node is a time node of the target infrared device, and the seventh target time node is a server time node when the background server obtains the sixth target time node;

[0053] Calculate the difference between the sixth target time node and the seventh target time node to obtain a second time difference;

[0054] Calculate the sum of the fifth target time node and the second time difference to obtain a sixth target time node;

[0055] Determine that the infrared image collected by the target infrared device at the sixth target time node is the target infrared image.

[0056] Specifically, since the time between the sensor device and the infrared device is not synchronized, it is necessary to confirm the time node of the target infrared device when the time node of the sensor device is the second target time node. In some implementations, the second target time node is 15:19, the third target time node is 15:20, and the fourth target time node is 15:22, indicating that the time of the sensor device is 2 minutes slower than the time of the backend server (the first target time difference is -2 minutes). When the time node of the sensor device is 15:19 (the second target time node), the time node of the backend server is 15:21 (the fifth target time node), the sixth target time node is 15:16, and the seventh target time node is 15:11, which means that the time of the infrared device is 4 minutes faster than that of the background server (the second time difference is 4 minutes). Therefore, when the time node of the background server is 15:21 (the fifth target time node), the time node of the infrared device is 15:25 (the sixth target time node), that is, when the time node of the sensor device is 15:19 (the second target time node), the time node of the infrared device is 15:25 (the sixth target time node).

[0057] In an optional solution, after the above step S203, the above method further includes:

[0058] The above target infrared image is subjected to image enhancement processing and image noise reduction processing in sequence.

[0059] Specifically, image enhancement processing is performed on the target infrared image to enhance the contrast of the target infrared image and adjust the brightness of the target infrared image, thereby improving the accuracy of substation fire monitoring. Image noise reduction processing is performed on the target infrared image to remove noise in the target infrared image and improve the quality of the target infrared image, thereby further improving the accuracy of substation fire monitoring.

[0060] Step S204: determining whether a fire occurs in the target line to be tested at the second target time node based on the target infrared image.

[0061] Specifically, when the target line to be tested is a line to be tested that has a risk of fire at the second target time node, it is necessary to obtain and further verify whether a fire occurs in the target line to be tested based on an infrared image of the target line to be tested at the second target time node.

[0062] In an optional solution, the above step S204 can be implemented as follows:

[0063] Divide the target infrared image into a plurality of square areas of the same size;

[0064] Calculate the average grayscale values ​​of the pixels in each of the square grid areas to obtain a plurality of average grayscale values, wherein the average grayscale values ​​correspond to the square grid areas one by one;

[0065] When at least one of the above average grayscale values ​​is greater than a predetermined grayscale value, it is determined that a fire occurs in the target line to be tested at the second target time node.

[0066] Specifically, the target infrared image is divided into square areas of multiple sizes, and the average grayscale value of the pixel points in each square area is calculated to obtain the average grayscale value. If the average grayscale value is greater than the predetermined grayscale value, a fire occurs in the square area corresponding to the average grayscale value, and then it is determined that a fire occurs in the target line to be tested at the second target time node.

[0067] In an optional solution, after the above step S204, the above method includes:

[0068] In the event of a fire in the target line to be tested at the second target time node, controlling the target alarm device to sound and light alarm, the target alarm device being the alarm device on the target line to be tested;

[0069] The feedback information is sent to a display device so that the display device displays the feedback information, wherein the feedback information indicates that a fire has occurred in the target line to be tested, and the feedback information includes: the number of the substation and the number of the target line to be tested.

[0070] Specifically, an alarm device is installed on each line to be tested, and each alarm device is connected to the background server for communication. When a fire occurs in the target line to be tested at the second target time node, the target alarm device is controlled to give an audible and visual alarm to alert the staff, and feedback information is sent to the display device so that the display device displays the feedback information to further alert the staff.

[0071] In an optional solution, after the above step S204, the above method includes:

[0072] Acquire target meteorological information through the sensor device, the target meteorological information being the meteorological information of the target line to be tested at the second target time node, the meteorological information including: wind speed and wind direction;

[0073] Specifically, the sensor equipment also includes: a wind speed and direction sensor, which is used to obtain meteorological information of the line to be tested.

[0074] Obtaining the flammable parameter information of each electrical device on the target circuit to be tested, wherein the flammable parameter information includes: ignition temperature, combustion temperature, and auto-ignition temperature;

[0075] The meteorological information of the target line to be tested, the target infrared image, and the flammable parameter information of each of the electrical equipment on the target line to be tested are input into a fire path prediction model to obtain a fire path of the target line to be tested. The fire path prediction model is obtained by training a neural network with second training data, wherein each group of the second training data at least includes: the meteorological information of the line to be tested, the infrared image of the line to be tested, the flammable parameter information of each of the electrical equipment on the line to be tested, and the fire path of the line to be tested, obtained within a historical period. The fire path is a numbering sequence composed of numbers of each of the electrical equipment arranged in the order of occurrence of the fire.

[0076] Specifically, the fire path prediction model comprehensively considers the meteorological information of the target line to be tested, the target infrared image, and the flammable parameter information of each electrical device on the target line to be tested, and outputs the fire path of the target line to be tested.

[0077] Through the above embodiment, first, the sensor data of the line to be tested at the first target time node is obtained, and then, based on the sensor data, the line to be tested with a fire risk at the second target time node, that is, the target line to be tested, is screened out. After that, it is only necessary to obtain an infrared image of the target line to be tested at the second target time node. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining a video of each line. In addition, the sensor data transmission only needs to occupy fewer network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0078] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0079] The embodiment of the present application also provides a substation fire monitoring device. It should be noted that the substation fire monitoring device of the embodiment of the present application can be used to execute the substation fire monitoring method provided by the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0080] The following is an introduction to the substation fire monitoring device provided in the embodiment of the present application.

[0081] Figure 2is a structural block diagram of a substation fire monitoring device according to an embodiment of the present application. Figure 2 As shown, the device comprises:

[0082] A first acquisition unit 10 is used to acquire multiple groups of target sensor data through the above sensor device;

[0083] The target sensor data is sensor data of the line to be tested at the first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested;

[0084] Specifically, the substation includes multiple lines to be tested, each of the above-mentioned lines to be tested is installed with a sensor device, and an infrared device is installed directly above each of the above-mentioned lines to be tested. Each of the above-mentioned sensor devices and each of the above-mentioned infrared devices are communicatively connected to the background server, wherein the sensor devices include: a temperature sensor, a current sensor, a voltage sensor, a leakage current sensor and a wind speed and direction sensor. The temperature sensor is used to obtain the temperature of the line to be tested, the current sensor is used to obtain the current of the line to be tested, the voltage sensor is used to obtain the voltage of the line to be tested, the leakage current sensor is used to obtain the residual current of the line to be tested, and the wind speed and direction sensor is used to obtain the meteorological information of the line to be tested.

[0085] A first determination unit 20 is used to determine whether there is a target line to be tested according to the above multiple sets of target sensor data;

[0086] The target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node;

[0087] Specifically, there may be multiple target circuits to be tested.

[0088] In an optional solution, the first determining unit includes:

[0089] An input module is used to input each group of the target sensor data into the temperature prediction model to obtain multiple target temperatures, wherein one target temperature corresponds to one of the lines to be tested, and one target temperature is the temperature of the corresponding line to be tested at the second target time node. The temperature prediction model is obtained by training a neural network using multiple groups of first training data, wherein each group of the first training data includes: the sensor data of one of the lines to be tested at one of the sensor time nodes, and the temperature of the line to be tested at the next sensor time node of the sensor time node;

[0090] Specifically, in some implementations, the first target time node is 11:13, and the second target time node is 11:14. The sensor data of each line to be tested at 11:13 is input into the prediction model to obtain the temperature of each line to be tested at 11:14.

[0091] The first determining module is used to determine that the circuit to be tested corresponding to the target temperature is the target circuit to be tested when the target temperature is greater than a predetermined temperature.

[0092] Specifically, when the temperature of the line under test at the second target time node (target temperature) is greater than the predetermined temperature, it is determined that the line under test has a fire risk at the second target time node, that is, the line under test is determined to be the target line under test.

[0093] The second acquisition unit 30 is used to acquire a target infrared image through a target infrared device when the target circuit to be tested exists;

[0094] Wherein, the target infrared device is the infrared device on the target circuit to be tested, and the target infrared image is the infrared image of the target circuit to be tested at the second target time node;

[0095] In an optional solution, the above device also includes:

[0096] A third acquisition unit is used to acquire a third target time node and a fourth target time node through a target sensor device, wherein the target sensor device is the sensor device on the target line to be tested, the third target time node is the sensor time node next to the second target time node, the fourth target time node is the server time node when the background server acquires the third target time node, and the server time node is the time node of the background server;

[0097] A first calculation unit, used to calculate the difference between the third target time node and the fourth target time node to obtain a first time difference;

[0098] A second calculation unit is used to calculate the difference between the second target time node and the first time difference to obtain a fifth target time node;

[0099] The fourth acquisition unit is used to acquire a sixth target time node through the target infrared device and acquire a seventh target time node, wherein the sixth target time node is an infrared time node, the infrared time node is a time node of the target infrared device, and the seventh target time node is a server time node when the background server acquires the sixth target time node;

[0100] A third calculation unit is used to calculate the difference between the sixth target time node and the seventh target time node to obtain a second time difference;

[0101] a fourth calculation unit, configured to calculate the sum of the fifth target time node and the second time difference to obtain a sixth target time node;

[0102] The third determining unit is used to determine that the infrared image collected by the target infrared device at the sixth target time node is the target infrared image.

[0103] Specifically, since the time between the sensor device and the infrared device is not synchronized, it is necessary to confirm the time node of the target infrared device when the time node of the sensor device is the second target time node. In some implementations, the second target time node is 15:19, the third target time node is 15:20, and the fourth target time node is 15:22, indicating that the time of the sensor device is 2 minutes slower than the time of the backend server (the first target time difference is -2 minutes). When the time node of the sensor device is 15:19 (the second target time node), the time node of the backend server is 15:21 (the fifth target time node), the sixth target time node is 15:16, and the seventh target time node is 15:11, which means that the time of the infrared device is 4 minutes faster than that of the background server (the second time difference is 4 minutes). Therefore, when the time node of the background server is 15:21 (the fifth target time node), the time node of the infrared device is 15:25 (the sixth target time node), that is, when the time node of the sensor device is 15:19 (the second target time node), the time node of the infrared device is 15:25 (the sixth target time node).

[0104] In an optional solution, the above device also includes:

[0105] The processing unit is used to perform image enhancement processing and image noise reduction processing on the above target infrared image in sequence.

[0106] Specifically, image enhancement processing is performed on the target infrared image to enhance the contrast of the target infrared image and adjust the brightness of the target infrared image, thereby improving the accuracy of substation fire monitoring. Image noise reduction processing is performed on the target infrared image to remove noise in the target infrared image and improve the quality of the target infrared image, thereby further improving the accuracy of substation fire monitoring.

[0107] The second determination unit 40 is used to determine whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image.

[0108] Specifically, when the target line to be tested is a line to be tested that has a risk of fire at the second target time node, it is necessary to obtain and further verify whether a fire occurs in the target line to be tested based on an infrared image of the target line to be tested at the second target time node.

[0109] In an optional solution, the second determining unit includes:

[0110] A division module, used for dividing the target infrared image into a plurality of square areas of the same size;

[0111] A calculation module, used to calculate the average grayscale values ​​of the pixels in each of the above-mentioned grid areas, to obtain a plurality of average grayscale values, wherein the average grayscale values ​​correspond to the above-mentioned grid areas one by one;

[0112] The second determination module is used to determine that a fire occurs in the target line to be tested at the second target time node when at least one of the above average grayscale values ​​is greater than a predetermined grayscale value.

[0113] Specifically, the target infrared image is divided into square areas of multiple sizes, and the average grayscale value of the pixel points in each square area is calculated to obtain the average grayscale value. If the average grayscale value is greater than the predetermined grayscale value, a fire occurs in the square area corresponding to the average grayscale value, and then it is determined that a fire occurs in the target line to be tested at the second target time node.

[0114] In an optional solution, the above device includes:

[0115] A control unit, used to control a target alarm device to give an audible and visual alarm when a fire occurs in the target line to be tested at the second target time node, wherein the target alarm device is an alarm device on the target line to be tested;

[0116] The sending unit is used to send feedback information to a display device so that the display device displays the feedback information. The feedback information indicates that a fire occurs in the target line to be tested. The feedback information includes: the number of the substation and the number of the target line to be tested.

[0117] Specifically, an alarm device is installed on each line to be tested, and each alarm device is connected to the background server for communication. When a fire occurs in the target line to be tested at the second target time node, the target alarm device is controlled to give an audible and visual alarm to alert the staff, and feedback information is sent to the display device so that the display device displays the feedback information to further alert the staff.

[0118] In an optional solution, the above device includes:

[0119] A fifth acquisition unit is used to acquire target meteorological information through the sensor device, the target meteorological information is the meteorological information of the target line to be tested at the second target time node, and the meteorological information includes: wind speed and wind direction;

[0120] Specifically, the sensor equipment also includes: a wind speed and direction sensor, which is used to obtain meteorological information of the line to be tested.

[0121] A sixth acquisition unit is used to acquire the flammable parameter information of each electrical device on the target circuit to be tested, wherein the flammable parameter information includes: ignition temperature, combustion temperature, and auto-ignition temperature;

[0122] An input unit is used to input the above-mentioned meteorological information of the above-mentioned target line to be tested, the above-mentioned target infrared image, and the above-mentioned flammable parameter information of each of the above-mentioned electrical equipment on the above-mentioned target line to be tested into a fire path prediction model to obtain the fire path of the above-mentioned target line to be tested, wherein the above-mentioned fire path prediction model is obtained by training a neural network with second training data, wherein each group of the above-mentioned second training data at least includes: the above-mentioned meteorological information of the above-mentioned line to be tested, the infrared image of the above-mentioned line to be tested, the above-mentioned flammable parameter information of each of the above-mentioned electrical equipment on the above-mentioned line to be tested, and the above-mentioned fire path of the above-mentioned line to be tested, obtained within a historical period, wherein the above-mentioned fire path is a numbering sequence composed of the numbers of the above-mentioned electrical equipment arranged in the order of occurrence of the fire.

[0123] Specifically, the fire path prediction model comprehensively considers the meteorological information of the target line to be tested, the target infrared image, and the flammable parameter information of each electrical device on the target line to be tested, and outputs the fire path of the target line to be tested.

[0124] Through the above embodiment, first, the sensor data of the line to be tested at the first target time node is obtained, and then, based on the sensor data, the line to be tested with a fire risk at the second target time node, that is, the target line to be tested, is screened out. After that, it is only necessary to obtain an infrared image of the target line to be tested at the second target time node. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining a video of each line. In addition, the sensor data transmission only needs to occupy fewer network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0125] The above-mentioned substation fire monitoring device includes a processor and a memory, and the above-mentioned first acquisition unit, first determination unit, second acquisition unit, second determination unit, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions. The above-mentioned modules are all located in the same processor; or, the above-mentioned modules are located in different processors in the form of any combination.

[0126] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be provided, and the problem of poor timeliness of the substation fire monitoring method in the prior art can be solved by adjusting kernel parameters.

[0127] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0128] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the substation fire monitoring method.

[0129] Specifically, the substation fire monitoring method includes:

[0130] Step S201, acquiring multiple groups of target sensor data through the above sensor device;

[0131] The target sensor data is sensor data of the line to be tested at the first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested;

[0132] Step S202, determining whether there is a target line to be tested according to the above multiple sets of target sensor data;

[0133] The target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node;

[0134] Step S203, when the target circuit to be tested exists, obtaining a target infrared image through a target infrared device;

[0135] Wherein, the target infrared device is the infrared device on the target circuit to be tested, and the target infrared image is the infrared image of the target circuit to be tested at the second target time node;

[0136] Step S204: determining whether a fire occurs in the target line to be tested at the second target time node based on the target infrared image.

[0137] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the substation fire monitoring method is executed when the program is run.

[0138] Specifically, the substation fire monitoring method includes:

[0139] Step S201, acquiring multiple groups of target sensor data through the above sensor device;

[0140] The target sensor data is sensor data of the line to be tested at the first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested;

[0141] Step S202, determining whether there is a target line to be tested according to the above multiple sets of target sensor data;

[0142] The target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node;

[0143] Step S203, when the target circuit to be tested exists, obtaining a target infrared image through a target infrared device;

[0144] Wherein, the target infrared device is the infrared device on the target circuit to be tested, and the target infrared image is the infrared image of the target circuit to be tested at the second target time node;

[0145] Step S204: determining whether a fire occurs in the target line to be tested at the second target time node based on the target infrared image.

[0146] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0147] Step S201, acquiring multiple groups of target sensor data through the above sensor device;

[0148] The target sensor data is sensor data of the line to be tested at the first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested;

[0149] Step S202, determining whether there is a target line to be tested according to the above multiple sets of target sensor data;

[0150] The target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node;

[0151] Step S203, when the target circuit to be tested exists, obtaining a target infrared image through a target infrared device;

[0152] Wherein, the target infrared device is the infrared device on the target circuit to be tested, and the target infrared image is the infrared image of the target circuit to be tested at the second target time node;

[0153] Step S204: determining whether a fire occurs in the target line to be tested at the second target time node based on the target infrared image.

[0154] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0155] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0160] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0161] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0162] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0163] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0164] 1) In the substation fire monitoring method of the present application, first, the sensor data of the line to be tested at the first target time node is obtained, and then, based on the sensor data, the line to be tested that has a fire risk at the second target time node, that is, the target line to be tested, is screened out. After that, it is only necessary to obtain an infrared image of the target line to be tested at the second target time node. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining a video of each line. In addition, the sensor data transmission only needs to occupy a small amount of network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0165] 2) In the substation fire monitoring device of the present application, first, the sensor data of the line to be tested at the first target time node is obtained, and then, based on the sensor data, the line to be tested that has a fire risk at the second target time node, that is, the target line to be tested, is screened out. After that, it is only necessary to obtain an infrared image of the target line to be tested at the second target time node. Finally, based on this infrared image, it is determined whether a fire has occurred in the target line to be tested, without obtaining the video of each line. In addition, the sensor data transmission only needs to occupy less network resources, thereby improving the timeliness of substation fire monitoring, thereby solving the problem of poor timeliness of the substation fire monitoring method in the prior art.

[0166] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A substation fire monitoring method, characterized in that: The substation includes a plurality of lines to be tested, each of the lines to be tested is equipped with a sensor device, an infrared device is installed directly above each of the lines to be tested, each of the sensor devices and each of the infrared devices are communicatively connected to a background server, and the method is applied to the background server, and the method includes: Acquire multiple groups of target sensor data through the sensor device, wherein the target sensor data is sensor data of the line to be tested at a first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested; Determine whether there is a target line to be tested according to the multiple sets of target sensor data, the target line to be tested being the line to be tested having a fire risk at a second target time node, the second target time node being the sensor time node next to the first target time node; In the case where the target line to be tested exists, a target infrared image is acquired through a target infrared device, wherein the target infrared device is the infrared device on the target line to be tested, and the target infrared image is an infrared image of the target line to be tested at the second target time node; According to the target infrared image, it is determined whether a fire occurs in the target line to be tested at the second target time node.

2. The method according to claim 1, characterized in that In the process of determining whether there is a target circuit to be tested according to the multiple sets of target sensor data, the method includes: Input each group of the target sensor data into the temperature prediction model respectively to obtain multiple target temperatures, wherein one target temperature corresponds to one of the lines to be tested, and one target temperature is the temperature of the corresponding line to be tested at the second target time node, and the temperature prediction model is obtained by training a neural network using multiple groups of first training data, wherein each group of the first training data includes: the sensor data of one of the lines to be tested at one of the sensor time nodes, and the temperature of the line to be tested at the sensor time node next to the one of the sensor time nodes; When the target temperature is greater than a predetermined temperature, the circuit to be tested corresponding to the target temperature is determined as the target circuit to be tested.

3. The method according to claim 1, characterized in that Before acquiring a target infrared image through a target infrared device, the method includes: Acquire a third target time node and a fourth target time node through a target sensor device, wherein the target sensor device is the sensor device on the target line to be tested, the third target time node is the sensor time node next to the second target time node, the fourth target time node is the server time node when the background server acquires the third target time node, and the server time node is the time node of the background server; Calculating a difference between the third target time node and the fourth target time node to obtain a first time difference; Calculate the difference between the second target time node and the first time difference to obtain a fifth target time node; Acquire a sixth target time node through the target infrared device, and acquire a seventh target time node, wherein the sixth target time node is an infrared time node, the infrared time node is a time node of the target infrared device, and the seventh target time node is the server time node when the backend server acquires the sixth target time node; Calculating a difference between the sixth target time node and the seventh target time node to obtain a second time difference; Calculate the sum of the fifth target time node and the second time difference to obtain a sixth target time node; Determine that the infrared image collected by the target infrared device at the sixth target time node is the target infrared image.

4. The method according to claim 1, characterized in that: Determining whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image includes: Dividing the target infrared image into a plurality of square areas of the same size; Calculating the average grayscale values ​​of the pixels in each of the square grid areas to obtain a plurality of average grayscale values, wherein the average grayscale values ​​correspond to the square grid areas one by one; When at least one of the average grayscale values ​​is greater than a predetermined grayscale value, it is determined that a fire occurs in the target line to be tested at the second target time node.

5. The method according to claim 1, characterized in that An alarm device is installed on each of the lines to be tested, and each of the alarm devices is in communication connection with the background server. After determining whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image, the method further includes: When a fire occurs in the target line to be tested at the second target time node, control a target alarm device to give an audible and visual alarm, wherein the target alarm device is an alarm device on the target line to be tested; Feedback information is sent to a display device so that the display device displays the feedback information, wherein the feedback information indicates that a fire occurs in the target line to be tested, and the feedback information includes: the number of the substation and the number of the target line to be tested.

6. The method according to claim 1, characterized in that After determining whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image, the method further includes: Acquiring target meteorological information through the sensor device, wherein the target meteorological information is meteorological information of the target line to be tested at the second target time node, and the meteorological information includes: wind speed and wind direction; Acquire flammable parameter information of each electrical device on the target circuit to be tested, wherein the flammable parameter information includes: ignition temperature, combustion temperature, and auto-ignition temperature; The meteorological information of the target line to be tested, the target infrared image, and the flammable parameter information of each electrical device on the target line to be tested are input into a fire path prediction model to obtain a fire path of the target line to be tested, wherein the fire path prediction model is obtained by training a neural network with second training data, wherein each group of the second training data at least includes: the meteorological information of the line to be tested, the infrared image of the line to be tested, the flammable parameter information of each electrical device on the line to be tested, and the fire path of the line to be tested, obtained within a historical period, wherein the fire path is a numbering sequence composed of numbers of each electrical device arranged in the order of occurrence of the fire.

7. The method according to claim 1, characterized in that After acquiring the target infrared image by the target infrared device, the method further includes: The target infrared image is subjected to image enhancement processing and image noise reduction processing in sequence.

8. A substation fire monitoring device, characterized in that: The substation includes a plurality of lines to be tested, each of which is equipped with a sensor device, and an infrared device is installed directly above each of which, and each of which is connected to a backend server for communication. The device is applied to the backend server, and includes: A first acquisition unit is used to acquire multiple groups of target sensor data through the sensor device, wherein the target sensor data is sensor data of the line to be tested at a first target time node, the first target time node is any sensor time node, the sensor time node is a time node of the sensor device, and the sensor data includes: the temperature of the line to be tested, the current of the line to be tested, the voltage of the line to be tested, and the residual current of the line to be tested; A first determining unit is configured to determine whether there is a target line to be tested according to the multiple sets of target sensor data, wherein the target line to be tested is the line to be tested that has a fire risk at a second target time node, and the second target time node is the sensor time node next to the first target time node; A second acquisition unit is used to acquire a target infrared image through a target infrared device when the target line to be tested exists, wherein the target infrared device is the infrared device on the target line to be tested, and the target infrared image is an infrared image of the target line to be tested at the second target time node; The second determination unit is used to determine whether a fire occurs in the target line to be tested at the second target time node according to the target infrared image.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the substation fire monitoring method according to any one of claims 1 to 7 is implemented.

10. A substation fire monitoring system, characterized in that: The system comprises: A plurality of sensor devices, the substation includes a plurality of lines to be tested, one sensor device corresponds to one of the lines to be tested, and the sensor device is installed on the corresponding line to be tested; A plurality of infrared devices, one of the infrared devices corresponds to one of the circuits to be tested, and the infrared device is installed directly above the corresponding circuit to be tested; A plurality of alarm devices, one of the alarm devices corresponds to one of the lines to be tested, and the alarm device is installed on the corresponding line to be tested; Display devices; The background server is respectively connected to each of the sensor devices, and is respectively connected to each of the infrared devices, and is respectively connected to each of the alarm devices, and is respectively connected to the display device. The background server is used to execute the substation fire monitoring method described in any one of claims 1 to 7.

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