A method, device, equipment and medium for calculating temperature field distribution of electric power equipment

Abstract

The present invention discloses a method, device, equipment and medium for calculating the temperature field distribution of electric equipment, which is used to solve the technical problems that the existing finite element method based temperature field distribution calculation efficiency is low, and the data-driven temperature field distribution fast calculation method is easy to produce large calculation errors locally. It includes: calculating the equipment temperature field distribution data of the electric equipment under multiple preset boundary value conditions; dividing the non-fluid material area of ​​the electric equipment into non-fluid modules; extracting the fluid flow rate of the fluid domain of the electric equipment; dividing the fluid domain into a high-flow rate fluid module and a low-flow rate fluid module; respectively obtaining the temperature data of the non-fluid module, the high-flow rate fluid module, and the low-flow rate fluid module under each boundary value condition; respectively establishing the mapping relationship between each boundary value condition and the temperature data of the non-fluid module, the high-flow rate fluid module, and the low-flow rate fluid module; according to the boundary value conditions and the mapping relationship, obtaining the target equipment temperature field distribution corresponding to the boundary value conditions to be analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power equipment, and in particular to a method, device, equipment and medium for calculating the temperature field distribution of electric power equipment. Background Art

[0002] The key technology of multi-physics simulation is one of the important technologies for the development and application of digital twins. It solves the multi-physics distribution characteristics of the entire device under certain boundary conditions through the coupling and constitutive relationship between physical fields, and then evaluates and analyzes the device based on the field quantity distribution. However, most of the multi-physics solutions are partial differential equations or integral forms, and are more complicated when it comes to coupling. The solution process takes a long time and has poor convergence. It often has high requirements for hard addition. At the same time, the solution time measured in hours or days does not meet the requirements of digital twins for entity mirroring. Therefore, it is of great significance to develop a real-time multi-physics distribution fast extraction and output technology to ensure that multi-physics simulation can be accurately output in real time when applied in digital twin systems, which is of great significance for online evaluation and analysis of equipment and status warning.

[0003] The multi-physics fast calculation method based on machine learning has been widely proposed. It constructs the fitting relationship between the boundary conditions and each node during simulation based on a finite set of multi-physics simulation grid node data, so as to quickly obtain the distribution results under other different conditions. However, this method often incorporates all the results of multi-physics simulation into the machine learning data set, and the learning method and parameters used do not take into account the characteristics of multi-physics distribution. Therefore, large local errors will occur during the calculation process; at the same time, the machine learning model is constructed for all data, and the model is large and costly, which also restricts the output efficiency of the calculation results to a certain extent. Summary of the invention

[0004] The present invention provides a method, device, equipment and medium for calculating the temperature field distribution of electric equipment, which are used to solve the technical problems that the existing finite element method-based temperature field distribution calculation efficiency is low, and the data-driven temperature field distribution fast calculation method is prone to produce large calculation errors locally.

[0005] The present invention provides a method for calculating the temperature field distribution of electric power equipment, comprising:

[0006] Calculating the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions;

[0007] Acquire a non-fluid material region of the power equipment, and divide the non-fluid material region into a plurality of non-fluid modules;

[0008] Extracting the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data;

[0009] Dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate;

[0010] Respectively acquiring the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each of the boundary conditions from the equipment temperature field distribution data;

[0011] Establishing mapping relationships between the boundary conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data respectively;

[0012] The boundary value condition to be analyzed is obtained, and according to the boundary value condition and the mapping relationship, the temperature field distribution of the target device corresponding to the boundary value condition to be analyzed is obtained.

[0013] Optionally, the step of obtaining the non-fluid material area of ​​the power equipment and dividing the non-fluid material area into a plurality of non-fluid modules includes:

[0014] Acquire a non-fluid material region of the power device;

[0015] The non-fluid material region is divided into a plurality of non-fluid modules based on a closed boundary condition.

[0016] Optionally, the equipment temperature field distribution data includes coordinates, temperature and flow rate.

[0017] Optionally, the step of dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate comprises:

[0018] Obtaining the maximum flow velocity in the fluid domain;

[0019] determining a flow rate threshold value according to the maximum flow rate;

[0020] Divide the area where the fluid flow rate reaches the flow rate threshold into a high flow rate fluid module;

[0021] The area where the fluid flow rate is less than the flow rate threshold is divided into a low flow rate fluid module.

[0022] Optionally, the step of respectively establishing a mapping relationship between each boundary value condition of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data comprises:

[0023] Constructing a mapping relationship between the boundary conditions of the non-fluid module and the temperature data by a linear fitting method;

[0024] Constructing a mapping relationship between the boundary conditions of the low-flow-rate fluid module and the temperature data by a polynomial regression method;

[0025] The mapping relationship between the boundary conditions of the high-velocity fluid and the temperature data is constructed by a neural network learning method.

[0026] The present invention also provides a device for calculating the temperature field distribution of electric power equipment, comprising:

[0027] The equipment temperature field distribution data calculation module is used to calculate the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions;

[0028] A non-fluid module division module, used for obtaining a non-fluid material area of ​​the electric power equipment and dividing the non-fluid material area into a plurality of non-fluid modules;

[0029] A fluid flow rate extraction module, used to extract the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data;

[0030] A fluid module division module, used for dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate;

[0031] A temperature data acquisition module, used to respectively acquire the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each of the boundary conditions from the equipment temperature field distribution data;

[0032] A mapping relationship establishment module, used to establish mapping relationships between the boundary conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data respectively;

[0033] The target device temperature field distribution acquisition module is used to acquire the boundary value condition to be analyzed, and acquire the target device temperature field distribution corresponding to the boundary value condition to be analyzed according to the boundary value condition and the mapping relationship.

[0034] Optionally, the non-fluid module is divided into modules, comprising:

[0035] A non-fluid material area acquisition submodule, used to acquire the non-fluid material area of ​​the power equipment;

[0036] The non-fluid module division submodule is used to divide the non-fluid material area into a plurality of non-fluid modules based on a closed boundary condition.

[0037] Optionally, the fluid module division module comprises:

[0038] A maximum flow rate acquisition submodule, used to acquire the maximum flow rate of the fluid domain;

[0039] A flow rate threshold determination submodule, used to determine a flow rate threshold according to the maximum flow rate;

[0040] A high-flow-rate fluid module division submodule, used for dividing the area where the fluid flow rate reaches the flow rate threshold into a high-flow-rate fluid module;

[0041] The low-flow-rate fluid module division submodule is used to divide the area where the fluid flow rate is less than the flow rate threshold into a low-flow-rate fluid module.

[0042] The present invention also provides an electronic device, the device comprising a processor and a memory:

[0043] The memory is used to store program code and transmit the program code to the processor;

[0044] The processor is used to execute the method for calculating the temperature field distribution of electric power equipment as described in any one of the above items according to the instructions in the program code.

[0045] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store program codes, and the program codes are used to execute the method for calculating the temperature field distribution of electric power equipment as described in any one of the above items.

[0046] It can be seen from the above technical scheme that the present invention has the following advantages: The present invention discloses a method for calculating the temperature field distribution of an electric equipment, comprising: calculating the equipment temperature field distribution data corresponding to the electric equipment under preset multiple sets of boundary value conditions; obtaining the non-fluid material area of ​​the electric equipment, and dividing the non-fluid material area into a number of non-fluid modules; extracting the fluid flow rate of the fluid domain of the electric equipment according to the equipment temperature field distribution data; dividing the fluid domain into a number of high-flow rate fluid modules and low-flow rate fluid modules according to the fluid flow rate; obtaining the temperature data of the non-fluid module, the high-flow rate fluid module, and the low-flow rate fluid module under each boundary value condition from the equipment temperature field distribution data; establishing a mapping relationship between each boundary value condition and the temperature data of the non-fluid module, the high-flow rate fluid module, and the low-flow rate fluid module; obtaining the boundary value condition to be analyzed, and obtaining the target equipment temperature field distribution corresponding to the boundary value condition to be analyzed according to the boundary value condition and the mapping relationship. The present invention divides regions according to the multi-physical field distribution and field solution characteristics of power equipment, matches specific different fast calculation methods to different regions, so that the physical field characteristics and the fast calculation methods are interrelated, which can effectively improve the accuracy of the data-driven fast calculation method and avoid distortion of local calculation results. On the basis of regional division, the present invention realizes the fast matching between the boundary value conditions and the equipment temperature field distribution by mapping, thereby improving the calculation efficiency of the temperature field distribution of power equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0048] Figure 1 A flowchart of a method for calculating the temperature field distribution of electric power equipment provided by an embodiment of the present invention;

[0049] Figure 2 A flowchart of a method for calculating the temperature field distribution of electric power equipment provided by another embodiment of the present invention;

[0050] Figure 3 A schematic diagram of a neural network provided by an embodiment of the present invention;

[0051] Figure 4 A structural block diagram of a device for calculating the temperature field distribution of electric power equipment provided by an embodiment of the present invention;

[0052] Figure 5 A schematic diagram of the division of a high-flow rate fluid module and a low-flow rate fluid module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The embodiments of the present invention provide a method, device, equipment and medium for calculating the temperature field distribution of power equipment, which are used to solve the technical problems that the existing finite element method-based temperature field distribution calculation efficiency is low, and the data-driven temperature field distribution fast calculation method is prone to produce large calculation errors locally.

[0054] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] See also Figure 1 , Figure 1 A flowchart of the steps of a method for calculating the temperature field distribution of electric equipment provided by an embodiment of the present invention.

[0056] The present invention provides a method for calculating the temperature field distribution of electric power equipment, which may specifically include the following steps:

[0057] Step 101, calculating the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions;

[0058] In the embodiment of the present invention, the boundary conditions are operating conditions that can affect the temperature field distribution of the power equipment during simulation, including current waveform, ambient temperature, ambient humidity, wind speed, etc.

[0059] In the specific implementation, the electromagnetic-thermal-fluid coupling simulation calculation method can be used to calculate the power equipment under different boundary conditions Γ1, Γ2, ..., Γ n The corresponding equipment temperature field distribution data T1, T2, ..., T n .

[0060] The calculation process of the electromagnetic-thermal-fluid coupling simulation method is as follows:

[0061] Given the finite element simulation model, boundary conditions and initial calculation values, the magnetic field module in COMSOL Multiphysics is used to calculate the Joule loss considering the skin effect, and the node data is extracted and imported into ANSYS CFX as the heat source for fluid thermal analysis to calculate the temperature field distribution, and the material properties of the metal and fluid are corrected according to the initial calculation results. If the i-th iteration satisfies T i -T i-1 <δ, the calculation iteration is considered to have converged and the temperature field distribution result is stable. Otherwise, the Joule loss and temperature field distribution are recalculated until the convergence condition is met. The value of δ is 0.1K.

[0062] The temperature field distribution data under different boundary conditions can be obtained by scanning, that is, after inputting a combination (current waveform, ambient temperature, ambient humidity, wind speed), a set of temperature field distribution data is calculated and the results are stored, and then another set of combinations is input, and so on.

[0063] Step 102, obtaining a non-fluid material area of ​​the power equipment, and dividing the non-fluid material area into a plurality of non-fluid modules;

[0064] In the embodiment of the present invention, the interior of the power equipment includes a fluid material area and a non-fluid material area, and the non-fluid material is a component of each device. Taking the three-phase common box GIL as an example, the non-fluid material includes epoxy composite material for supporting insulators, aluminum alloy for current-carrying conductors, aluminum alloy for housings, etc.

[0065] According to the different materials and properties of the non-fluid material, the non-fluid material area can be divided into several non-fluid modules.

[0066] Step 103, extracting the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data;

[0067] The fluid domain is the area where the fluid materials in the power equipment are located, including gas, transformer oil, etc.

[0068] Fluid flow rate refers to the velocity of the fluid within the fluid domain.

[0069] In an embodiment of the present invention, the device temperature field distribution data may be expressed in the form of "coordinate-temperature-flow rate". Based on the device temperature field distribution data, the fluid flow rate of the fluid domain of the power equipment under each boundary value condition may be extracted.

[0070] Step 104, dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate;

[0071] According to the fluid flow rate, the fluid domain can be divided into several high-flow rate fluid modules and low-flow rate fluid modules.

[0072] In one example, the maximum flow rate of the fluid domain may be used as a reference, and a flow rate lower than the maximum flow rate may be selected as a basis for dividing the high flow rate fluid module and the low flow rate fluid module.

[0073] Step 105, respectively obtaining the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each boundary value condition from the equipment temperature field distribution data;

[0074] Step 106, respectively establish mapping relationships between boundary value conditions and temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module;

[0075] After obtaining the module division results of the power equipment under various boundary conditions (including non-fluid modules, high-flow fluid modules and low-flow fluid modules), the temperature data can be matched for each module according to the equipment temperature field distribution data. The mapping relationship between Γ and T under different boundary conditions of each module is established, and the mapping relationship model A1, A2...A is output. m , where m is the number of modules.

[0076] Step 107, obtaining the boundary value conditions to be analyzed, and obtaining the temperature field distribution of the target device corresponding to the boundary value conditions to be analyzed according to the boundary value conditions and the mapping relationship.

[0077] After the mapping relationship model is constructed, the specified boundary value conditions to be analyzed are input, and the mapping relationship of each module is applied to obtain the temperature field distribution A1(Γ x ), A2(Γ x ),……、A m (Γ x ).

[0078] Since the modeling is split according to each module in the process of building the mapping relationship, after calculating the temperature field distribution of each module under the boundary value condition to be analyzed, in order to restore the overall temperature field distribution of the power equipment, the results need to be spliced ​​together. Specifically, the output results of the mapping relationship model of each module can be reorganized according to the geometric relationship to obtain the temperature field distribution T under the boundary value condition to be analyzed. x .

[0079] The present invention divides regions according to the multi-physical field distribution and field solution characteristics of power equipment, matches specific different fast calculation methods to different regions, so that the physical field characteristics and fast calculation methods are interrelated, which can effectively improve the accuracy of data-driven fast calculation methods and avoid distortion of local calculation results. On the basis of regional division, the present invention realizes fast matching between boundary conditions and equipment temperature field distribution by mapping, thereby improving the calculation efficiency of power equipment temperature field distribution. .

[0080] See also Figure 2 , Figure 2 A flowchart of a method for calculating the temperature field distribution of electric power equipment provided by another embodiment of the present invention. Specifically, the following steps may be included:

[0081] Step 201, calculating the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions;

[0082] In the embodiment of the present invention, step 201 is the same as step 101, and the details may refer to the description of step 101, which will not be repeated here.

[0083] Step 202, obtaining a non-fluid material region of the power equipment;

[0084] Step 203, dividing the non-fluid material area into a plurality of non-fluid modules based on the closed boundary condition;

[0085] In the embodiment of the present invention, a non-fluid material region with a closed boundary may be regarded as a non-fluid module.

[0086] Step 204, extracting the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data;

[0087] In the embodiment of the present invention, the equipment temperature field distribution data may include coordinates, temperature and flow rate; according to the equipment temperature field distribution data, the fluid flow rate of the fluid domain of the power equipment under each boundary value condition may be extracted. .

[0088] Step 205, dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate;

[0089] According to the fluid flow rate, the fluid domain can be divided into several high-flow rate fluid modules and low-flow rate fluid modules.

[0090] In one example, the step of dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate may include the following sub-steps:

[0091] S51, obtaining the maximum flow velocity in the fluid domain;

[0092] S52, determining a flow rate threshold according to the maximum flow rate;

[0093] S53, dividing the area where the fluid flow rate reaches the flow rate threshold into a high flow rate fluid module;

[0094] S54, dividing the area where the fluid flow rate is less than the flow rate threshold into a low flow rate fluid module.

[0095] In a specific implementation, the maximum flow rate of the fluid domain can be used as a reference, and a flow rate lower than the maximum flow rate can be selected as a flow rate threshold, so as to divide the high flow rate fluid module and the low flow rate fluid module according to the flow rate threshold. Among them, the flow rate threshold can be 80% of the maximum flow rate. In addition, those skilled in the art can also select other values ​​according to actual needs, and the embodiment of the present invention does not specifically limit this.

[0096] Furthermore, after dividing the fluid modules according to the flow rate threshold, the minimum scale rectangle surrounding the fluid module (high flow rate fluid module, low flow rate fluid module) can also be used as a criterion. When the matrix boundary intersects with the fluid boundary layer, the boundary layer is converted into a fluid boundary to standardize the shape of the fluid module. Figure 5 Module 6 shown.

[0097] Step 206, respectively obtaining temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each boundary value condition from the equipment temperature field distribution data;

[0098] Step 207, respectively establish mapping relationships between the boundary conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data;

[0099] After obtaining the module division results of the power equipment under various boundary conditions (including non-fluid modules, high-flow fluid modules and low-flow fluid modules), the temperature data can be matched for each module according to the equipment temperature field distribution data. The mapping relationship between Γ and T under different boundary conditions of each module is established, and the mapping relationship model A1, A2...A is output. m , where m is the number of modules.

[0100] In one example, the steps of establishing mapping relationships between the boundary conditions of the non-fluid module, the high-flow rate fluid module, and the low-flow rate fluid module and the temperature data may specifically include the following sub-steps:

[0101] S71, constructing a mapping relationship between the boundary conditions of the non-fluid module and the temperature data by a linear fitting method;

[0102] In the specific implementation, the mapping model constructed by the linear fitting method is as follows:

[0103] t nj =k1Γ n1 +k2Γ n2 +k3Γ n3 +c

[0104] Among them, t nj is the temperature data, Γ n1 , Γ n2 , Γ n3 are different working conditions within a set of boundary conditions respectively, and k1, k2, k3, and c can be obtained by the least squares method.

[0105] S72, constructing a mapping relationship between the boundary conditions of the low-flow-rate fluid module and the temperature data by using a polynomial regression method;

[0106] In the specific implementation, the mapping model constructed by the polynomial regression method is as follows:

[0107]

[0108] Where ε is the observation error; Γ nq , Γ np are different working conditions within a set of boundary conditions; β0, β q , β qq , β pq is the fitting coefficient.

[0109] S73, constructing a mapping relationship between the boundary conditions of the high-velocity fluid and the temperature data through a neural network learning method.

[0110] In the specific implementation, by n As the input of the neural network, T' n =(t n1 ,t n2 ,t n3 ,…,t nj ) as the output of the neural network, training Figure 3 The neural network shown in Figure 2 is used to obtain the corresponding mapping model.

[0111] Step 208, obtaining the boundary value conditions to be analyzed, and obtaining the temperature field distribution of the target device corresponding to the boundary value conditions to be analyzed according to the boundary value conditions and the mapping relationship.

[0112] After the mapping relationship model is constructed, the specified boundary value conditions to be analyzed are input, and the mapping relationship of each module is applied to obtain the temperature field distribution A1(Γ x ), A2(Γ x ),……、A m (Γ x ).

[0113] Since the modeling is split according to each module in the process of building the mapping relationship, after calculating the temperature field distribution of each module under the boundary value condition to be analyzed, in order to restore the overall temperature field distribution of the power equipment, the results need to be spliced ​​together. Specifically, the output results of the mapping relationship model of each module can be reorganized according to the geometric relationship to obtain the temperature field distribution T under the boundary value condition to be analyzed. x .

[0114] The present invention divides regions according to the multi-physical field distribution and field solution characteristics of power equipment, matches specific different fast calculation methods to different regions, so that the physical field characteristics and fast calculation methods are interrelated, which can effectively improve the accuracy of data-driven fast calculation methods and avoid distortion of local calculation results. Furthermore, on the basis of regional division, the present invention constructs a high-level machine learning model for complex regions and selects linear methods for simple linear regions, so that the model construction and training time of the multi-physical field fast calculation method is short, and the model training cost with the overall data set as input is reduced. Furthermore, since the high-level multi-level machine learning model is large in size and the time required for word output is slower than that of the ordinary model, the regionalized module division is adopted to greatly reduce the amount of data required to output the high-level machine learning model, and the use of low-order linear models as a substitute can effectively shorten the output time of fast calculations and further improve the real-time performance of the calculation results.

[0115] See also Figure 4 , Figure 4 A structural block diagram of a device for calculating temperature field distribution of electric power equipment provided in an embodiment of the present invention.

[0116] An embodiment of the present invention provides a device for calculating the temperature field distribution of an electric power device, comprising:

[0117] The equipment temperature field distribution data calculation module 401 is used to calculate the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions;

[0118] A non-fluid module division module 402 is used to obtain a non-fluid material area of ​​the power equipment and divide the non-fluid material area into a plurality of non-fluid modules;

[0119] The fluid flow rate extraction module 403 is used to extract the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data;

[0120] The fluid module division module 404 is used to divide the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate;

[0121] The temperature data acquisition module 405 is used to respectively acquire the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each boundary value condition from the equipment temperature field distribution data;

[0122] A mapping relationship establishing module 406 is used to establish mapping relationships between the boundary value conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data;

[0123] The target device temperature field distribution acquisition module 407 is used to acquire the boundary value conditions to be analyzed, and acquire the target device temperature field distribution corresponding to the boundary value conditions to be analyzed according to the boundary value conditions and the mapping relationship.

[0124] In the embodiment of the present invention, the non-fluid module division module 402 includes:

[0125] A non-fluid material area acquisition submodule is used to acquire the non-fluid material area of ​​the power equipment;

[0126] The non-fluid module division submodule is used to divide the non-fluid material area into several non-fluid modules based on the closed boundary condition.

[0127] In the embodiment of the present invention, the fluid module division module 404 includes:

[0128] A maximum flow rate acquisition submodule is used to obtain the maximum flow rate of the fluid domain;

[0129] A flow rate threshold determination submodule, used to determine a flow rate threshold according to a maximum flow rate;

[0130] A high-flow-rate fluid module division submodule, used for dividing an area where the fluid flow rate reaches a flow rate threshold into a high-flow-rate fluid module;

[0131] The low-flow-rate fluid module division submodule is used to divide the area where the fluid flow rate is less than the flow rate threshold into a low-flow-rate fluid module.

[0132] In the embodiment of the present invention, the mapping relationship establishing module 406 includes:

[0133] A first mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the non-fluid module and the temperature data by a linear fitting method;

[0134] The second mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the low flow velocity fluid module and the temperature data by using a polynomial regression method;

[0135] The third mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the high-flow rate fluid and the temperature data through a neural network learning method.

[0136] An embodiment of the present invention further provides an electronic device, the device comprising a processor and a memory:

[0137] The memory is used to store the program code and transmit the program code to the processor;

[0138] The processor is used to execute the method for calculating the temperature field distribution of electric power equipment according to the instructions in the program code.

[0139] The embodiment of the present invention further provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the method for calculating the temperature field distribution of electric power equipment according to the embodiment of the present invention.

[0140] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0141] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0142] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take 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.

[0143] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the 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 terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal 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.

[0144] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including 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.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0146] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0147] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal 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, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0148] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the temperature field distribution of power equipment, characterized in that: include: Calculating the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions; Acquire a non-fluid material region of the power equipment, and divide the non-fluid material region into a plurality of non-fluid modules; Extracting the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data; Dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate; Respectively acquiring the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each of the boundary conditions from the equipment temperature field distribution data; Establishing mapping relationships between the boundary conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data respectively; Obtaining a boundary value condition to be analyzed, and obtaining a temperature field distribution of a target device corresponding to the boundary value condition to be analyzed according to the boundary value condition and the mapping relationship; Wherein, the step of respectively establishing the mapping relationship between the boundary value conditions of the non-fluid module, the high flow rate fluid module, and the low flow rate fluid module and the temperature data comprises: Constructing a mapping relationship between the boundary conditions of the non-fluid module and the temperature data by a linear fitting method; Constructing a mapping relationship between the boundary conditions of the low-flow-rate fluid module and the temperature data by a polynomial regression method; Constructing a mapping relationship between the boundary conditions of the high-velocity fluid and the temperature data through a neural network learning method; Among them, the mapping model constructed by the linear fitting method is as follows: ； Among them, t nj is the temperature data, , , are different working conditions within a set of boundary conditions, respectively, and k1, k2, k3, and c can be obtained by the least squares method; The mapping model constructed by the polynomial regression method is as follows: ； in, is the observation error; , are different working conditions within a set of boundary conditions; , , , is the fitting coefficient; Will As the input of the neural network, T' n =( t n1 , t n2 , t n3 ,…, t nj ) is used as the output of the neural network, and the neural network model is trained to construct the mapping relationship between the boundary conditions of high-velocity fluid and the temperature data.

2. The method according to claim 1, characterized in that The step of obtaining the non-fluid material area of ​​the power equipment and dividing the non-fluid material area into a plurality of non-fluid modules comprises: Acquire a non-fluid material region of the power device; The non-fluid material region is divided into a plurality of non-fluid modules based on a closed boundary condition.

3. The method according to claim 1, characterized in that The equipment temperature field distribution data includes coordinates, temperature and flow rate.

4. The method according to claim 1, characterized in that: The step of dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate comprises: Obtaining the maximum flow velocity in the fluid domain; determining a flow rate threshold value according to the maximum flow rate; Divide the area where the fluid flow rate reaches the flow rate threshold into a high flow rate fluid module; The area where the fluid flow rate is less than the flow rate threshold is divided into a low flow rate fluid module.

5. A device for calculating the temperature field distribution of electric power equipment, characterized in that: include: The equipment temperature field distribution data calculation module is used to calculate the equipment temperature field distribution data corresponding to the power equipment under the preset multiple groups of boundary value conditions; A non-fluid module division module, used for obtaining a non-fluid material area of ​​the electric power equipment and dividing the non-fluid material area into a plurality of non-fluid modules; A fluid flow rate extraction module, used to extract the fluid flow rate of the fluid domain of the power equipment according to the equipment temperature field distribution data; A fluid module division module, used for dividing the fluid domain into a plurality of high-flow-rate fluid modules and low-flow-rate fluid modules according to the fluid flow rate; A temperature data acquisition module, used to respectively acquire the temperature data of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module under each of the boundary conditions from the equipment temperature field distribution data; A mapping relationship establishment module, used to establish mapping relationships between the boundary conditions of the non-fluid module, the high-flow-rate fluid module, and the low-flow-rate fluid module and the temperature data respectively; The target device temperature field distribution acquisition module is used to acquire the boundary value condition to be analyzed, and acquire the target device temperature field distribution corresponding to the boundary value condition to be analyzed according to the boundary value condition and the mapping relationship; The mapping relationship establishment module includes: A first mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the non-fluid module and the temperature data by a linear fitting method; The second mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the low flow rate fluid module and the temperature data by using a polynomial regression method; The third mapping relationship construction submodule is used to construct a mapping relationship between the boundary conditions of the high-velocity fluid and the temperature data through a neural network learning method; Among them, the mapping model constructed by the linear fitting method is as follows: ； Among them, t nj is the temperature data, , , are different working conditions within a set of boundary conditions, respectively, and k1, k2, k3, and c can be obtained by the least squares method; The mapping model constructed by the polynomial regression method is as follows: ； in, is the observation error; , are different working conditions within a set of boundary conditions; , , , is the fitting coefficient; Will As the input of the neural network, T' n =( t n1 , t n2 , t n3 ,…, t nj ) is used as the output of the neural network, and the neural network model is trained to construct the mapping relationship between the boundary conditions of high-velocity fluid and the temperature data.

6. The device according to claim 5, characterized in that The non-fluid module division module includes: A non-fluid material area acquisition submodule, used to acquire the non-fluid material area of ​​the power equipment; The non-fluid module division submodule is used to divide the non-fluid material area into a plurality of non-fluid modules based on a closed boundary condition.

7. The device according to claim 5, characterized in that The fluid module division module comprises: A maximum flow rate acquisition submodule, used to acquire the maximum flow rate of the fluid domain; A flow rate threshold determination submodule, used to determine a flow rate threshold according to the maximum flow rate; A high-flow-rate fluid module division submodule, used for dividing the area where the fluid flow rate reaches the flow rate threshold into a high-flow-rate fluid module; The low-flow-rate fluid module division submodule is used to divide the area where the fluid flow rate is less than the flow rate threshold into a low-flow-rate fluid module.

8. An electronic device, characterized in that: The device comprises a processor and a memory: The memory is used to store program codes and transmit the program codes to the processor; The processor is used to execute the method for calculating the temperature field distribution of electric power equipment according to any one of claims 1 to 4 according to the instructions in the program code.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program codes, and the program codes are used to execute the method for calculating the temperature field distribution of electric power equipment according to any one of claims 1 to 4.

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