Transformer fire risk detection method and device and readable storage medium

Abstract

The invention belongs to the technical field of disaster prevention and reduction of a power system, and relates to a transformer fire risk detection method and device and a readable storage medium. Obtaining characteristic parameters of each part in the transformer, combustion thermodynamic characteristic parameters of combustibles in the transformer and load data of each part of the transformer under the combustion mechanical characteristic parameters of the combustibles based on the transformer type and the voltage grade; constructing a transformer three-dimensional model based on the operation parameters and the characteristic parameters of each component in the transformer, and meshing the transformer three-dimensional model to obtain a transformer three-dimensional grid model; performing dynamic simulation on the three-dimensional grid model of the transformer based on the load data of each part of the transformer under the combustion mechanical characteristic parameters of the combustible, and outputting a fire risk index of each part in the transformer; and calculating a to-be-detected transformer fire risk index based on the fire risk index of each component and the fire risk propagation coefficient among the components.

Description

Technical Field

[0001] The present invention relates to the technical field of disaster prevention and mitigation of power systems, and in particular to a transformer fire risk detection method, device, and computer-readable storage medium. Background Art

[0002] Transformer fires are one of the most serious catastrophic accidents in power systems, and fires are often accompanied by the spread of toxic smoke and cascading failures in the power grid. Therefore, transformer fire risk detection is crucial to the stable operation of transformers and power systems.

[0003] The existing methods for transformer fire risk detection are usually based on the overall operating parameters of the transformer to obtain a three-dimensional transformer model. The load data of the transformer under the combustion thermodynamic characteristic parameters of the combustible materials inside it is then obtained, and the three-dimensional transformer model is dynamically simulated to directly output the risk value of the transformer fire under the current operating parameters. However, since transformers of different types and voltage levels have different internal components, the characteristic parameters of each component are affected differently by the voltage level and transformer type. At the same time, the load data of each component under the combustion thermodynamic characteristic parameters of the internal combustibles are also different. In actual use, each component reaching the load data that causes a fire may cause a transformer fire. The existing method directly ignores the fire risk assessment of each component in transformers of different types and voltage levels, resulting in a deviation of more than 30% in the final fire risk detection results; at the same time, the combustion thermodynamic characteristic parameters of the internal combustibles of transformers of different types and voltage levels are different, which also leads to different load data of transformers of different types and voltage levels under the combustion thermodynamic characteristic parameters of their internal combustibles. The existing method directly relies on the empirical values ​​in the existing literature and uses the same combustion thermodynamic characteristic parameters of the internal combustibles for transformers of all types and voltage levels. This also leads to errors in the load data obtained and the actual situation, thereby affecting the accuracy of the fire risk detection results.

[0004] In summary, the existing transformer fire risk detection method ignores the differences in the combustion thermodynamic characteristic parameters of internal combustibles under transformer types and voltage levels. At the same time, it ignores the differences in characteristic parameters brought about by transformer types and voltage levels on its internal components and the impact of the fire risk probability of each component on the transformer fire risk detection results, resulting in large errors in the transformer fire risk detection results. Summary of the Invention

[0005] To this end, the technical problem to be solved by the present invention is to overcome the problem that the transformer fire risk detection method in the existing technology ignores the differences in the combustion thermodynamic characteristic parameters of internal combustibles under the transformer type and voltage level, and at the same time, ignores the differences in characteristic parameters brought about by the transformer type and voltage level on its internal components and the influence of the fire risk probability of each component on the fire risk detection results of the transformer, thereby resulting in large errors in the obtained transformer fire risk detection results.

[0006] To solve the above technical problems, the present invention provides a transformer fire risk detection method, comprising: Obtain the operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain the characteristic parameters of each component in the transformer, the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, and the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material; A three-dimensional transformer model is constructed based on the operating parameters and characteristic parameters of each component in the transformer, and the three-dimensional transformer model is meshed to obtain a three-dimensional transformer mesh model; Using unstructured grid dynamic encryption technology, the three-dimensional grid model of the transformer is dynamically simulated based on the load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials, thereby outputting the fire risk index of each component in the transformer; Based on the fire risk index of each component and the fire risk propagation coefficient between components, the fire risk index of the transformer to be tested is calculated.

[0007] Preferably, the transformer types include oil-immersed transformers and converter transformers; wherein the voltage levels of the oil-immersed transformers include 110kV and 330kV, and the voltage level of the converter transformers is ±800kV; The internal components of an oil-immersed transformer include the core, windings, oil pillow, bushings, and radiator; The internal components of the converter transformer include the core, winding, oil pillow, bushing, radiator, valve-side bushing and smoothing reactor module.

[0008] Preferably, the characteristic parameter of the sleeve is the sleeve length, which is calculated as follows: , in, Indicates the length of the casing; Indicates the voltage level conversion coefficient. When the voltage level is 110kV, , when the voltage level is 330kV, , when the voltage level is ±800kV, ; Indicates voltage level; The characteristic parameter of the radiator is the heat dissipation surface area, which is calculated as follows: , in, Indicates the heat dissipation surface area; Indicates the heat dissipation efficiency factor of the transformer. When the transformer is an oil-immersed transformer, , when the transformer is a commutation transformer, ; Indicates the total heat loss power.

[0009] Preferably, the process of obtaining the combustion thermodynamic characteristic parameters of the combustible material inside the transformer includes: Obtain the maximum heat release rate of ordinary mineral oil in a 110kV oil-immersed transformer and the ignition temperature of the insulation board; Obtain the maximum heat release rate of Karamay oil and the activation energy of thermal decomposition of insulation paper in a 330kV oil-immersed transformer; Obtain the flash point of Karamay oil and the decomposition temperature of epoxy resin in converter transformers with a voltage level of ±800kV.

[0010] Preferably, the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material include the critical failure temperature, maximum heat release rate, and exposure dose safety threshold of each component.

[0011] Preferably, the fire risk index of each component is expressed as: , in, Indicates the Fire risk index of each component; Indicates the risk factor of fire due to temperature overload; Indicates the The temperature of each component; Indicates the Safety temperature threshold of each component; Indicates the The critical failure temperature of each component under the combustion mechanics characteristic parameters of combustibles; Indicates the risk factor of fire due to heat release rate; Indicates the Heat release rate of each component; Indicates the The maximum heat release rate of each component under the combustion mechanical characteristic parameters of the combustible; Indicates the risk factor of fire due to exposure dose; Indicates the Exposure dose to each component; Indicates the The exposure dose safety threshold of each component under the combustion mechanical characteristic parameters of combustibles.

[0012] Preferably, the calculation formula for the fire risk index of the transformer to be detected is: , in, Indicates the fire risk index of the transformer to be detected; Indicates the Fire risk index of each component; Indicates the Parts and The fire risk transmission coefficient between components.

[0013] Preferably, after obtaining the fire risk index of the transformer to be detected, the method further includes obtaining a three-dimensional thermal map based on the fire risk index of each component and the fire risk index of the transformer to be detected, thereby visualizing the fire risk distribution of the transformer to be detected.

[0014] The present invention also provides a transformer fire risk detection device, comprising: A data acquisition module is used to obtain the operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain the characteristic parameters of each component in the transformer, the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, and the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material; The model building and networking module is used to build a three-dimensional model of the transformer based on the operating parameters and characteristic parameters of each component in the transformer, and to grid the three-dimensional model of the transformer to obtain a three-dimensional grid model of the transformer; The component fire risk index output module is used to dynamically simulate the transformer's three-dimensional grid model based on the load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials using unstructured grid dynamic encryption technology, thereby outputting the fire risk index of each component in the transformer; The transformer fire risk index output module is used to calculate the fire risk index of the transformer to be detected based on the fire risk index of each component and the fire risk propagation coefficient between each component.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned transformer fire risk detection method are implemented.

[0016] The fire risk detection method provided in the present application obtains the characteristic parameters of the internal components and the combustion thermodynamic characteristic parameters of the internal combustibles based on the type and voltage level of the transformer, so that the load data of each component in the transformer of different types and voltage levels under the combustion mechanical characteristic parameters of the combustibles can be obtained; a three-dimensional model of the transformer is constructed based on the operating parameters and characteristic parameters of each component corresponding to the transformer type and voltage level. At this time, the internal components and characteristic parameters of the three-dimensional model of the transformer are more consistent with the actual transformer to be detected, thereby improving the accuracy of the fire risk detection results output by the three-dimensional model of the transformer during simulation; further, a three-dimensional grid model of the transformer is obtained by gridding the three-dimensional model of the transformer; and the unstructured grid dynamic encryption technology is used to obtain the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustibles. The load data under the mechanical characteristic parameters is used to dynamically simulate the three-dimensional grid model of the transformer. Since the model is constructed based on the parameters of each component, the fire risk index of each component in the transformer can be output during simulation. Not only the voltage level of the type of transformer to be detected is considered, but also the fire risk detection is refined to each component of the transformer to achieve component-level fire risk assessment; finally, based on the fire risk index of each component and the fire risk propagation coefficient between each component, the fire risk index of the transformer to be detected is obtained. When obtaining the fire risk index of the transformer, not only the fire risk index of each component is considered, but also the fire risk propagation coefficient between each component, that is, the coupling effect between each component is considered, which further improves the accuracy of the transformer fire risk detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments of the present invention in conjunction with the accompanying drawings, wherein: Figure 1 Flowchart of the transformer fire risk detection method provided for this application; Figure 2 A flowchart for constructing a three-dimensional transformer model provided in this application; Figure 3 Component-level and system-level risk detection flow chart provided for this application. DETAILED DESCRIPTION

[0018] The present invention will be further described below with reference to the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it. However, the embodiments are not intended to limit the present invention.

[0019] See also Figure 1 , Figure 1 The figure shows a flow chart of the transformer fire risk detection method provided by this application, which specifically includes: S10: Obtain operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain characteristic parameters of each component in the transformer, combustion thermodynamic characteristic parameters of combustibles inside the transformer, and load data of each component of the transformer under the combustion mechanical characteristic parameters of combustibles.

[0020] S20: constructing a three-dimensional model of the transformer based on the operating parameters and characteristic parameters of each component in the transformer, and meshing the three-dimensional model of the transformer to obtain a three-dimensional mesh model of the transformer.

[0021] S30: Using the unstructured grid dynamic encryption technology, the three-dimensional grid model of the transformer is dynamically simulated based on the load data of each component of the transformer under the combustion mechanical characteristic parameters of combustible materials, thereby outputting the fire risk index of each component in the transformer.

[0022] S40: Calculate the fire risk index of the transformer to be detected based on the fire risk index of each component and the fire risk propagation coefficient between the components.

[0023] Specifically, the transformer types include oil-immersed transformers and converter transformers; among them, the voltage levels of the oil-immersed transformers include 110kV and 330kV, and the voltage level of the converter transformer is ±800kV.

[0024] The internal components of an oil-immersed transformer include the core, windings, oil pillow, bushings, and radiator; The internal components of the converter transformer include the core, winding, oil pillow, bushing, radiator, valve-side bushing and smoothing reactor module.

[0025] Specifically, since the bushing length is affected by the voltage level of the transformer, and the heat dissipation efficiency factor of the radiator is affected by the type of transformer, the present application calculates the bushing length and the heat dissipation surface area of ​​the radiator based on the type and voltage level of the transformer, thereby accurately distinguishing transformers of different types and voltage levels in terms of component structure and parameters.

[0026] In some embodiments of the present application, the characteristic parameter of the sleeve is the sleeve length, which is calculated as follows: , in, Indicates the length of the casing; Indicates the voltage level conversion coefficient. When the voltage level is 110kV, , when the voltage level is 330kV, , when the voltage level is ±800kV, ; Indicates voltage level; The characteristic parameter of the radiator is the heat dissipation surface area, which is calculated as follows: , in, Indicates the heat dissipation surface area; Indicates the heat dissipation efficiency factor of the transformer. When the transformer is an oil-immersed transformer, , when the transformer is a commutation transformer, ; Indicates the total heat loss power.

[0027] The characteristic parameter of the valve-side bushing and smoothing reactor module is the arc explosion probability function, which is expressed as: .

[0028] Furthermore, the process of obtaining the combustion thermodynamic characteristic parameters of the combustible material inside the transformer includes: Obtain the maximum heat release rate of ordinary mineral oil in a 110kV oil-immersed transformer and the ignition temperature of the insulation board; Specifically, the maximum heat release rate of ordinary mineral oil is 180kW / m 2 The ignition temperature of insulating cardboard is 320℃.

[0029] Obtain the maximum heat release rate of Karamay oil and the activation energy of thermal decomposition of insulation paper in a 330kV oil-immersed transformer; Specifically, the maximum heat release rate of 45# Karamay oil in a 330kV oil-immersed transformer is 150kW / m 2 , Nomex insulation paper pyrolysis activation energy .

[0030] Obtain the flash point of Karamay oil and the decomposition temperature of epoxy resin in converter transformers with a voltage level of ±800kV.

[0031] Specifically, the flash point of No. 50 Karamay oil in ±800kV converter transformer is greater than 135℃, and the decomposition temperature of epoxy resin is .

[0032] Optionally, in the actual acquisition process of the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, there may be a deviation between the characteristic parameters measured by the sensor and the actual values. Therefore, in some embodiments of the present application, an incremental Bayesian optimization algorithm is introduced to correct the obtained characteristic parameters so that they are close to the actual characteristic parameter values. Specifically, the characteristic parameter correction formula is expressed as: , in, Indicates the sensor weight for obtaining characteristic parameters; Indicates the corrected characteristic parameters; Indicates the initial value of the characteristic parameter obtained by the sensor; Indicates the real-time characteristic parameter value obtained by the sensor; Indicates the aging time of data parameters; Represents the time decay factor, which determines the decay rate of the exponential function.

[0033] Furthermore, the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material include the critical failure temperature, maximum heat release rate, and exposure dose safety threshold of each component.

[0034] Optionally, in some other embodiments of the present application, the load data of the component windings in the 110 kV transformer further includes a temperature rise curve ( ), the load data of the oil pillow component in the 330kV transformer also includes the oil flow rate threshold ( ), the load data of the valve side bushing of the ±800kV converter transformer also includes the short-circuit current ( ) and insulator flashover probability model.

[0035] Furthermore, in some embodiments of the present application, the initial grid density can be set based on the voltage level of the transformer, so as to mesh the three-dimensional model of the transformer. Specifically, the initial grid size of the 110kV transformer is 50mm, the initial grid size of the 330kV transformer is 30mm, and the initial grid size of the ±800kV transformer is 20mm.

[0036] Specifically, the fire risk index of each component output by dynamic simulation is expressed as: , in, Indicates the Fire risk index of each component; Indicates the risk factor of fire due to temperature overload; Indicates the The temperature of each component; Indicates the Safety temperature threshold of each component; Indicates the The critical failure temperature of each component under the combustion mechanics characteristic parameters of combustibles; Indicates the risk factor of fire due to heat release rate; Indicates the The heat release rate of each component is used to reflect the combustion intensity; Indicates the The maximum heat release rate of each component under the combustion mechanical characteristic parameters of the combustible; Indicates the risk factor of fire due to exposure dose; Indicates the The exposure dose of each component is used to quantify the cumulative harm to the human body caused by toxic gas inhalation or thermal radiation; Indicates the The exposure dose safety threshold of each component under the combustion mechanical characteristic parameters of combustibles.

[0037] Optionally, 、 and The specific value of can be determined based on the improved hierarchical analysis method. In a specific example of this application, , , .

[0038] Furthermore, the calculation formula for the fire risk index of the transformer to be detected is: , in, Indicates the fire risk index of the transformer to be detected; Indicates the Fire risk index of each component; Indicates the Parts and The fire risk transmission coefficient between components is used to quantify the chain risk caused by the interaction between multiple components.

[0039] In a specific example of the present application, for a 110kV transformer, the fire risk propagation coefficient between the oil pillow and the bushing is 0.15, the fire risk propagation coefficient between the radiator and the winding in a 330kV transformer is 0.18, and the fire risk propagation coefficient between the converter oil and the valve hall in a ±800kV transformer is 0.25. The fire risk propagation coefficient between any two components can be determined through correlation analysis of historical fire cases.

[0040] Furthermore, after obtaining the fire risk index of the transformer to be detected, a three-dimensional heat map is obtained based on the fire risk index of each component and the fire risk index of the transformer to be detected, thereby realizing visualization of the fire risk distribution of the transformer to be detected.

[0041] Optionally, the positioning results of fire risk components can be achieved based on the three-dimensional thermal map, thereby outputting corresponding recommended measures.

[0042] like Figure 2 The figure shows the flow chart of building the transformer 3D model provided by this application. Figure 3The figure shows the component-level and system-level risk detection flow chart provided by the present application. As can be seen from the figure, the present application takes into account the component parameters of different types and voltage levels when constructing the three-dimensional model of the transformer. Furthermore, component-level fire risk detection and system-level fire risk detection are performed based on the three-dimensional model, and the fire risk index of the transformer type, voltage level, and internal components are comprehensively considered to obtain high-precision transformer fire risk detection results.

[0043] Based on the above transformer fire risk detection method, the embodiment of the present application further provides a transformer fire risk detection device, which specifically includes: A data acquisition module is used to obtain the operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain the characteristic parameters of each component in the transformer, the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, and the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material; The model building and networking module is used to build a three-dimensional model of the transformer based on the operating parameters and characteristic parameters of each component in the transformer, and to grid the three-dimensional model of the transformer to obtain a three-dimensional grid model of the transformer; The component fire risk index output module is used to dynamically simulate the transformer's three-dimensional grid model based on the load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials using unstructured grid dynamic encryption technology, thereby outputting the fire risk index of each component in the transformer; The transformer fire risk index output module is used to calculate the fire risk index of the transformer to be detected based on the fire risk index of each component and the fire risk propagation coefficient between each component.

[0044] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned transformer fire risk detection method are implemented.

[0045] The technical solution of the present application is described in more detail below in conjunction with a plurality of embodiments. However, it should be understood that the following embodiments and comparative examples are only for explaining and illustrating the technical solution and do not limit the scope of the present application.

[0046] Example 1 of the present application provides a method for detecting fire risk of a 110kV transformer: When building the model, we input a voltage level of 110 kV and an oil-immersed type, which automatically loaded the characteristic parameters of each component. The number of winding turns N = 620, and the oil channel spacing d = 3.2 mm, The number of mesh nodes generated when meshing the transformer 3D model is 5.8×10 5 ; After GPU acceleration, it takes 0.7 hours to output the hotspot temperature under overload conditions. (Traditional method: 6.2 hours, error +22%); Risk assessment results: Winding FRI=82, System FRI=68; The decision report recommends shortening the oil chromatography detection cycle to 15 days.

[0047] Example 2 of the present application provides a method for detecting fire risk of a 330kV transformer: When building the model, we input a voltage level of 330 kV and an oil-immersed type, which automatically loaded the characteristic parameters of each component. The oil flow rate v = 0.8 m / s (lower than the threshold of 1.2 m / s) and the radiator surface area S = 28 m2 were used. Dynamic simulation: The local temperature rise rate of the oil pillow caused by oil flow stagnation reached 12°C / min, and the system FRI was 79, triggering a level 2 warning.

[0048] Example 3 of the present application provides a fire risk detection method for ±800kV transformers: When building the model, input voltage level ±800kV, type commutation, and then automatically load the characteristic parameters of each component, among which the input short-circuit current The air flow field in the valve hall is coupled with the arc plasma, and the simulation time is 3.8 hours.

[0049] Risk detection results: valve side casing FRI=91, explosion equivalent , decision output: the emergency oil drain valve start-up delay needs to be less than 3s.

[0050] In the method provided in this application, model construction time is shortened by 90%, and fast switching across types / voltage levels is supported. At the same time, self-correction of thermal properties ensures that the error of key parameters is ≤5%, which is better than the industry standard (IEEE 979). Finally, structured reporting reduces operation and maintenance response time from hours to minutes, quantifying transformer risks.

[0051] 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 take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] 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 block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 produce 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.

[0053] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0054] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0055] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A transformer fire risk detection method, characterized in that: include: Obtain the operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain the characteristic parameters of each component in the transformer, the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, and the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material; A three-dimensional transformer model is constructed based on the operating parameters and characteristic parameters of each component in the transformer, and the three-dimensional transformer model is meshed to obtain a three-dimensional transformer mesh model; Using unstructured grid dynamic encryption technology, the three-dimensional grid model of the transformer is dynamically simulated based on the load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials, thereby outputting the fire risk index of each component in the transformer; Based on the fire risk index of each component and the fire risk propagation coefficient between components, the fire risk index of the transformer to be tested is calculated.

2. The transformer fire risk detection method according to claim 1, characterized in that: Transformer types include oil-immersed transformers and converter transformers; the voltage levels of oil-immersed transformers include 110kV and 330kV, and the voltage level of converter transformers is ±800kV; The internal components of an oil-immersed transformer include the core, windings, oil pillow, bushings, and radiator; The internal components of the converter transformer include the core, winding, oil pillow, bushing, radiator, valve-side bushing and smoothing reactor module.

3. The transformer fire risk detection method according to claim 2, characterized in that: The characteristic parameter of the casing is the casing length, which is calculated as follows: ， in, Indicates the length of the casing; Indicates the voltage level conversion coefficient. When the voltage level is 110kV, , when the voltage level is 330kV, , when the voltage level is ±800kV, ; Indicates voltage level; The characteristic parameter of the radiator is the heat dissipation surface area, which is calculated as follows: ， in, Indicates the heat dissipation surface area; Indicates the heat dissipation efficiency factor of the transformer. When the transformer is an oil-immersed transformer, , when the transformer is a commutation transformer, ; Indicates the total heat loss power.

4. The transformer fire risk detection method according to claim 1, characterized in that: The process of obtaining the combustion thermodynamic characteristic parameters of the combustible materials inside the transformer includes: Obtain the maximum heat release rate of ordinary mineral oil in a 110kV oil-immersed transformer and the ignition temperature of the insulation board; Obtain the maximum heat release rate of Karamay oil and the activation energy of thermal decomposition of insulation paper in a 330kV oil-immersed transformer; Obtain the flash point of Karamay oil and the decomposition temperature of epoxy resin in converter transformers with a voltage level of ±800kV.

5. The transformer fire risk detection method according to claim 1, characterized in that: The load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials include the critical failure temperature, maximum heat release rate, and exposure dose safety threshold of each component.

6. The transformer fire risk detection method according to claim 1, characterized in that: The fire risk index of each component is expressed as: ， in, Indicates the Fire risk index of each component; Indicates the risk factor of fire due to temperature overload; Indicates the The temperature of each component; Indicates the Safety temperature threshold of each component; Indicates the The critical failure temperature of each component under the combustion mechanics characteristic parameters of combustibles; Indicates the risk factor of fire due to heat release rate; Indicates the Heat release rate of each component; Indicates the The maximum heat release rate of each component under the combustion mechanical characteristic parameters of the combustible; Indicates the risk factor of fire due to exposure dose; Indicates the Exposure dose to each component; Indicates the The exposure dose safety threshold of each component under the combustion mechanical characteristic parameters of combustibles.

7. The transformer fire risk detection method according to claim 6, characterized in that: The calculation formula for the fire risk index of the transformer to be tested is: ， in, Indicates the fire risk index of the transformer to be detected; Indicates the Fire risk index of each component; Indicates the Parts and The fire risk transmission coefficient between components.

8. The transformer fire risk detection method according to claim 1, characterized in that: After obtaining the fire risk index of the transformer to be detected, the method further includes obtaining a three-dimensional thermal map based on the fire risk index of each component and the fire risk index of the transformer to be detected, thereby realizing visualization of the fire risk distribution of the transformer to be detected.

9. A transformer fire risk detection device, characterized in that: include: A data acquisition module is used to obtain the operating parameters of each component in the transformer to be tested, and based on the type and voltage level of the transformer to be tested, obtain the characteristic parameters of each component in the transformer, the combustion thermodynamic characteristic parameters of the combustible material inside the transformer, and the load data of each component of the transformer under the combustion mechanical characteristic parameters of the combustible material; The model building and networking module is used to build a three-dimensional model of the transformer based on the operating parameters and characteristic parameters of each component in the transformer, and to grid the three-dimensional model of the transformer to obtain a three-dimensional grid model of the transformer; The component fire risk index output module is used to dynamically simulate the transformer's three-dimensional grid model based on the load data of each transformer component under the combustion mechanical characteristic parameters of combustible materials using unstructured grid dynamic encryption technology, thereby outputting the fire risk index of each component in the transformer; The transformer fire risk index output module is used to calculate the fire risk index of the transformer to be detected based on the fire risk index of each component and the fire risk propagation coefficient between each component.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the transformer fire risk detection method according to any one of claims 1 to 8 are implemented.

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