Transformer winding overheating fault diagnosis method

Abstract

The embodiment of the invention discloses a transformer winding overheating fault diagnosis method, and relates to the technical field of power equipment state monitoring, and the method comprises the steps: building a temperature field model of a target transformer under a normal working condition and a plurality of preset winding overheating fault working conditions through a finite element simulation method, and obtaining a temperature field model of the target transformer based on a simulation result; calculating to obtain a group of fault temperature rise critical values corresponding to the positions of the winding sections; when the transformer runs on line, actual measurement temperature rise data of a plurality of positions on the surface of a box body of the transformer are obtained, and the actual measurement temperature rise data are compared with a fault temperature rise critical value so as to locate a winding section where an overheating fault occurs; for the fault section, solving an actual overheating temperature rise value of the fault section through an inversion calculation method by utilizing a preset transformer equivalent thermal circuit model and combining the actually measured top layer oil temperature and bottom layer oil temperature data; high-precision simulation is arranged offline, an efficient algorithm is used online, the diagnosis precision and efficiency are both considered, the accuracy is high, and the practicability is high.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power equipment state monitoring, and particularly relates to a transformer winding overheat fault diagnosis method. BACKGROUND

[0002] The transformer is the core equipment of the power system, and its safe and stable operation is crucial. The winding overheat is one of the most common progressive faults of the transformer, and if it is not found in time and accurately evaluated, it may lead to accelerated aging of the insulation and even cause serious accidents such as inter-turn short circuit.

[0003] At present, diagnosing the overheat fault of the transformer mainly relies on two types of methods. The first type is the finite element method, which can simulate the temperature distribution inside the transformer by constructing a fine two-dimensional or three-dimensional electromagnetic thermal coupling field model, so as to accurately calculate the temperature at any position. However, the modeling process of the finite element method is complex, the calculation amount is huge, and the requirement for computing resources is high, which leads to a long calculation time and makes it difficult to meet the demand for online and real-time diagnosis in engineering. The second type is the thermal circuit method, which simplifies the complex heat transfer problem into a simple circuit network for solving, and realizes fast calculation by simplifying each component of the transformer into a concentrated heat source and a thermal resistance. However, due to the over-simplification of the model, the thermal circuit method is difficult to accurately describe the subtle changes of the local temperature, resulting in a serious lack of accuracy in locating and quantifying the local overheat fault at a specific position.

[0004] Therefore, at present, there is a dilemma that the diagnostic accuracy and the calculation efficiency cannot be balanced, and a new type of fault diagnosis method is urgently needed, which can not only guarantee the accuracy of the diagnosis result, but also meet the real-time requirement of engineering application. SUMMARY

[0005] The main purpose of the present application is to provide a transformer winding overheat fault diagnosis method, which aims to solve the technical problems of low calculation efficiency and difficulty in online application when using the finite element method for diagnosis, and the lack of accuracy caused by model simplification when using the thermal circuit method for diagnosis.

[0006] To achieve the above-mentioned purpose, the first aspect of the present application provides a transformer winding overheat fault diagnosis method, which comprises:

[0007] A temperature field model of the target transformer under normal operating conditions and a plurality of preset winding overheat fault operating conditions is established by a finite element simulation method, and a group of fault temperature rise critical values corresponding to the positions of each winding section is calculated based on the simulation results of the temperature field model;

[0008] When the transformer is running online, the measured temperature rise data of a plurality of positions on the tank surface of the transformer are obtained, and the measured temperature rise data are compared with the fault temperature rise critical values to locate the winding section where the overheat fault occurs;

[0009] For the located fault section, the preset transformer equivalent thermal circuit model is used, and the measured top layer oil temperature and bottom layer oil temperature data are combined, and the actual overheat temperature rise value of the fault section is solved by an inversion calculation method.

[0010] The second aspect of the application provides a transformer winding overheat fault diagnosis system, comprising:

[0011] A data generation module is configured to establish a temperature field model of a target transformer under normal operating conditions and a plurality of preset winding overheat fault operating conditions by a finite element simulation method, and calculate a set of fault temperature rise critical values corresponding to positions of each winding section based on simulation results of the temperature field model.

[0012] A fault positioning module is configured to obtain measured temperature rise data of a plurality of positions on a tank surface of the target transformer when the transformer is online, and compare the measured temperature rise data with the fault temperature rise critical values to locate a winding section where an overheat fault occurs.

[0013] A fault quantification module is configured to use a preset transformer equivalent thermal circuit model for the located fault section, combine measured top layer oil temperature and bottom layer oil temperature data, and solve the actual overheat temperature rise value of the fault section by an inversion calculation method.

[0014] The third aspect of the application provides a computer readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform each step in the method of the first aspect.

[0015] The application provides a transformer winding overheat fault diagnosis method, which establishes a temperature field model of a target transformer under normal operating conditions and a plurality of preset winding overheat fault operating conditions by a finite element simulation method, and calculates a set of fault temperature rise critical values corresponding to positions of each winding section based on simulation results of the temperature field model. When the transformer is online, measured temperature rise data of a plurality of positions on a tank surface of the transformer are obtained, and the measured temperature rise data are compared with the fault temperature rise critical values to locate a winding section where an overheat fault occurs. For the located fault section, a preset transformer equivalent thermal circuit model is used, and measured top layer oil temperature and bottom layer oil temperature data are combined, and the actual overheat temperature rise value of the fault section is solved by an inversion calculation method.

[0016] The application has the following beneficial effects: 1. Precision and efficiency are considered: the application places the high-precision finite element simulation with a large amount of calculation in the offline stage, which is used to establish a reliable fault feature database, and only simple numerical comparison and efficient thermal circuit model calculation are needed in the online diagnosis stage, so that the engineering real-time requirement is met while the diagnosis precision is ensured by using the finite element method. 2. High diagnosis accuracy: the basis for fault positioning is derived from accurate finite element simulation, which ensures the reliability of positioning; the introduction of measured top and bottom oil temperatures in the fault quantization stage constrains and calibrates the thermal circuit model, significantly improves the accuracy of the inversion calculation, and realizes accurate evaluation of the fault severity. 3. Strong engineering practicability: the online diagnosis process has small amount of calculation and fast speed, and is easy to integrate into the existing transformer online monitoring system, which can provide clear decision support for operation and maintenance personnel and effectively prevent major accidents. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Among them:

[0019] Figure 1 A flowchart of a transformer winding overheat fault diagnosis method provided by an embodiment of the present application;

[0020] Figure 2 A structure schematic diagram of a two-dimensional finite element simulation model of a transformer single-phase winding provided by an embodiment of the present application;

[0021] Figure 3 A structure schematic diagram of an equivalent thermal circuit model provided by an embodiment of the present application;

[0022] Figure 4 A structure schematic diagram of a transformer winding overheat fault diagnosis system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] The embodiments of this application are described below with reference to the accompanying drawings.

[0027] Figure 1 This is a flowchart illustrating a method for diagnosing transformer winding overheating faults provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0028] 101. Using the finite element simulation method, a temperature field model of the target transformer under normal operating conditions and various preset winding overheating fault conditions is established. Based on the simulation results of the above temperature field model, a set of fault temperature rise critical values ​​corresponding to the location of each winding section are calculated.

[0029] The method in the embodiments of this application can be executed based on a transformer winding overheating fault diagnosis method device or system.

[0030] First, in this embodiment, a temperature field model of the target transformer under normal operating conditions and various preset winding overheating fault conditions can be established using the finite element method (FEM). The FEM method in this embodiment employs a two-dimensional axisymmetric model or a three-dimensional sector model for modeling. The preset winding overheating fault conditions may include conditions simulating inter-turn short-circuit faults or conditions simulating winding oil passage blockage faults.

[0031] In one optional implementation, step 101 specifically includes:

[0032] The electromagnetic thermal coupling unit, which includes the A-phase high-voltage winding, low-voltage winding, core side column, and enclosure, is selected as the target area from the three-dimensional geometric model of the target transformer.

[0033] A two-dimensional axisymmetric simplified model was established using polar coordinates, preserving the interlayer insulation and oil channel structure features of the windings, and setting material parameters and boundary conditions consistent with the actual model.

[0034] Specifically, a simplified two-dimensional axisymmetric model can be established by selecting key structural elements of the target transformer, and material parameters and boundary conditions consistent with the actual model can be set. Furthermore, mesh refinement can be performed to improve model accuracy. Then, rated load conditions can be applied to the model, and steady-state temperature field finite element calculations can be performed to extract temperature values ​​at key locations and generate temperature distribution curves under normal operating conditions.

[0035] Next, overheating fault conditions of the winding, such as inter-turn short circuits, can be simulated. The current excitation conditions in the fault area are adjusted, and the temperature field is solved using finite element analysis to obtain temperature distribution data under fault conditions and establish a fault temperature characteristic database. Finally, the temperature distribution data under normal and fault conditions are compared to determine the aforementioned critical value for fault temperature rise.

[0036] In an optional implementation, the above-mentioned simulated inter-turn short-circuit fault condition can be achieved by increasing the excitation current of a specific winding disc to a preset range of 150% to 500% of the rated value, which can be selected and set as needed.

[0037] 102. When the transformer is running online, acquire measured temperature rise data at multiple locations on the surface of the transformer tank, and compare the measured temperature rise data with the fault temperature rise threshold to locate the winding section where the overheating fault occurred.

[0038] Specifically, multiple surface temperature sensors can be installed at equal intervals along the vertical direction of the transformer tank, corresponding to each winding. These sensors can record the temperature rise at each measuring point relative to the ambient temperature while the transformer is running online, obtaining the actual measured temperature rise of the transformer to be diagnosed. These measured temperature rise data are then compared with pre-calculated fault temperature rise thresholds to locate the winding section where an overheating fault has occurred.

[0039] 103. For the identified fault section, the actual overheating temperature rise of the fault section is calculated by using a preset transformer equivalent thermal circuit model and combined with the measured top and bottom oil temperature data through inversion calculation.

[0040] Sensors can also be used to measure the top and bottom oil temperatures of the transformer.

[0041] Specifically, for the identified faulty section, the actual overheating temperature rise of the faulty section can be calculated by using a preset transformer equivalent thermal circuit model and measured top and bottom oil temperature data through inversion calculation.

[0042] In one optional implementation, the above inversion calculation method includes:

[0043] In the equivalent thermal circuit model described above, at the nodes representing the located fault sections, a virtual voltage source is introduced to characterize the unknown fault heat source, so as to construct a modified set of node voltage equations.

[0044] These virtual voltage sources physically represent unknown additional temperature rises caused by faults. To solve for these unknown virtual voltage sources, additional constraints need to be introduced. This application's embodiments utilize two key physical quantities that are easily and accurately measured: the transformer's top oil temperature and bottom oil temperature.

[0045] Further, optionally, the above inversion calculation method also includes:

[0046] An optimization problem is established based on the above-modified set of nodal voltage equations. The objective of this optimization problem is to minimize the difference between the top oil temperature and bottom oil temperature data calculated by the model and the measured top oil temperature and bottom oil temperature data.

[0047] Specifically, the characteristics of the aforementioned transformer equivalent thermal circuit model can be utilized to introduce a virtual voltage source, construct a modified set of nodal voltage equations, and formulate an optimization problem: using the top oil temperature T calculated by the model... top_calc and bottom oil temperature T bottom_calc Compared with the measured top oil T top_meas and bottom oil temperature T bottom_meas The objective is to minimize the difference between the two. The objective function J can be set as needed; for example, it can be defined as the square of the Euclidean distance between the two, i.e.:

[0048] J(Ux1,Ux2,Ux3)=(T top_calc -T top_meas ) 2 +(T bottom_calc -T bottom_meas ) 2 Among them, T top_calc and T bottom_calc It is a function of the unknowns Ux1, Ux2, and Ux3.

[0049] The top oil temperature is measured by a top oil temperature sensor, typically installed in the oil layer at the top of the transformer tank, usually near the tank cover or a high position on the side. The bottom oil temperature is measured by a bottom oil temperature sensor, installed at the bottom of the tank, near the radiator or the inlet of the oil circulation channel. These bottom and top oil temperature measurement points (top oil temperature sensor and bottom oil temperature sensor) are usually standard equipment on transformers.

[0050] Alternatively, the method can solve the above optimization problem by using gradient descent or particle swarm optimization algorithm to obtain the optimal solution of the above virtual voltage source, and use the optimal solution as the actual overheating temperature rise value of the above fault section.

[0051] Specifically, in this embodiment, the gradient descent method is used. This involves calculating the gradient of the objective function J with respect to Ux1, Ux2, and Ux3, and iteratively updating the values ​​of Ux1, Ux2, and Ux3 along the negative direction of the gradient until the objective function J converges to its minimum value. The optimal solution obtained after convergence is the best estimate of the actual overheating temperature rise of the core, low-voltage winding, and high-voltage winding in the i-th fault section.

[0052] Finally, the system can output diagnostic results, display the calculated fault location i and the corresponding overheating temperature rise values ​​Ux1, Ux2, and Ux3, and can trigger alarms and generate detailed diagnostic reports.

[0053] The entire online diagnostic process (steps 102 and 103) involves minimal computation and can typically be completed within minutes, thus enabling rapid and accurate diagnosis of transformer winding overheating faults while balancing precision and efficiency.

[0054] Figure 2 This is a schematic diagram of a two-dimensional finite element simulation model of a single-phase winding of a transformer, provided in an embodiment of this application.

[0055] like Figure 2 The diagram shows a simplified schematic of the transformer's internal structure, along with the model's boundary conditions for finite element simulation analysis. This model can be built using commercial finite element analysis software such as ANSYS or COMSOL Multiphysics. Figure 2 The key components and oil passage structure of the transformer are clearly marked, providing an intuitive reference for implementing the transformer winding overheating fault diagnosis method in the embodiments of this application.

[0056] The model's geometry accurately replicates the key physical components of the transformer, including the transformer core located on the model's central axis, and the low-voltage and high-voltage windings arranged concentrically around the core. To accurately simulate the oil circulation cooling path inside the transformer, the model meticulously depicts the longitudinal and transverse oil channels located between the low-voltage and high-voltage windings, and between the windings and the core and tank walls. The outermost boundary of the model is the tank wall, while the model's central axis is defined as a symmetrical boundary, thus utilizing axisymmetry to significantly reduce computational complexity.

[0057] For example, in step 101 above, based on Figure 2After the model's geometry is constructed, accurate material physical properties need to be assigned to each component. For example, the thermal conductivity, electrical conductivity, and density of the silicon steel sheets are set for the iron core; the thermal conductivity, resistivity, density, and specific heat capacity of the copper or aluminum wires are set for the low-voltage and high-voltage windings; corresponding insulation material parameters are set for insulating paperboard, support bars, etc.; and parameters such as density, viscosity, thermal conductivity, and specific heat capacity as a function of temperature are set for the transformer oil. Simultaneously, reasonable boundary conditions need to be set. For example, convective heat transfer boundary conditions with ambient air are set on the outer surface of the tank wall, and the heat transfer coefficient can be determined based on the ambient wind speed and temperature. After the model is established, a refined mesh is performed on the entire computational domain, especially in areas with drastic temperature gradient changes such as the windings and oil channels, where a denser mesh is used to ensure computational accuracy. For ease of subsequent analysis, the high-voltage and low-voltage windings are each divided into N independent pie cells along the axial direction (i.e., vertical direction), where N can be 30, indicating that each winding is subdivided into 30 segments.

[0058] Based on the aforementioned model structure and method description, another embodiment is given below to further introduce a more specific method flow for diagnosing transformer winding overheating faults.

[0059] Specifically, the method includes:

[0060] S1. Establish the finite element simulation model of the target transformer.

[0061] S11: Based on the actual structural parameters of the target transformer, select the target area from the corresponding three-dimensional geometric model for modeling. The target area includes: the high-voltage winding of phase A, the low-voltage winding, the iron core side column where the winding is located, and the electromagnetic thermal coupling unit composed of the box; divide the high-voltage winding and the low-voltage winding into the same N-panel respectively.

[0062] S12: Based on the selected target area, establish as follows Figure 2 The simplified two-dimensional axisymmetric model shown is not described in detail here. The mesh of this simplified two-dimensional axisymmetric model is refined to a mesh density of at least 200 elements / mm. 2 ;

[0063] S2. Finite element calculation of transformer temperature field under rated normal operating conditions.

[0064] S21: Apply rated load conditions to the above two-dimensional axisymmetric simplified model, including: setting the excitation currents of the high-voltage winding and the low-voltage winding to rated current values; setting the ambient temperature; and performing steady-state temperature field finite element calculations.

[0065] S22: Extract the temperature values ​​at points on the surface of the oil tank wall that are at the same height as the high-voltage winding discs, generate an axial temperature distribution curve, and record the temperature rise between these points and the ambient temperature as ΔT.norm =[△T1…△T] N The rated current value of each winding can be determined according to the parameters on the transformer nameplate.

[0066] S3. Finite element simulation of transformer winding overheating fault condition.

[0067] S31: Perform inter-turn short-circuit overheating fault simulation for each independent pie unit of the high-voltage winding: sequentially select a single pie unit as the fault pie; increase the current value of the fault pie to 150%-500% of the rated value; keep the current value of the non-faulty pie units at the rated value.

[0068] S32: Perform short-circuit fault simulation calculation: Based on the above two-dimensional axisymmetric simplified model, apply the adjusted current excitation conditions and perform finite element solution of the temperature field;

[0069] S33: Establish a fault temperature characteristic database: Obtain the temperature distribution of the fault patch and its adjacent areas after S32 calculation; record the temperature rise curves under different short-circuit conditions; store the location-fault temperature rise mapping relationship of each high-voltage winding fault condition, denoted as ΔT. H =[△T H1 …△T HN ];

[0070] S34: For the low-voltage winding, repeat steps S31-S32 above to obtain the location-fault temperature rise mapping relationship of the low-voltage winding fault condition, denoted as ΔT. L =[△T L1 …△T LN ];

[0071] S4. Determine the critical value of fault temperature rise based on the finite element analysis results.

[0072] The normal operating temperature distribution data obtained in step S2 is compared point by point with the temperature distribution data of the high-voltage winding and low-voltage winding under fault conditions in steps S33 and S34, according to spatial location, and ΔT is calculated respectively. H -△T norm , △T L -△T norm The critical value ΔT for the fault temperature rise was determined. C =[△T C1 …△T CN ], where △T C The element at each position in the vector is denoted as ΔT. H -△T norm With △T L -△T norm The larger value among the elements at the corresponding positions;

[0073] S5. Locate overheating faults based on finite element analysis results.

[0074] S51: N surface temperature sensors are installed at equal intervals along the vertical direction of the transformer tank, corresponding to each winding; the temperature rise of each measuring point relative to the ambient temperature is recorded to obtain the actual measured temperature rise ΔT of the target transformer to be diagnosed. M =[△T M1 ,…△T MN ];

[0075] S52: Compare the temperature rise vector ΔT at each temperature analysis point in order from bottom to top. M and the fault temperature rise critical value vector ΔT C ; until the element at the i-th temperature analysis point in these two vectors is found that satisfies △T Mi >△T Ci ;

[0076] S53: Otherwise, continue to traverse all nodes until the conditions described in S52 are met; this indicates that the segment corresponding to the element, i.e. the i-th winding segment, has experienced an overheating fault, and the winding segment where the transformer thermal defect fault is located can be located accordingly.

[0077] S6. Transformer thermal circuit modeling and parameter configuration.

[0078] S61, according to... Figure 3 Establish a thermal circuit calculation model of the internal thermal field of the transformer;

[0079] like Figure 3 A schematic diagram of an equivalent thermal circuit model is provided, wherein Φ IRON,i Φ is the equivalent current source for heating the iron core, and its magnitude is the heating power value of the i-th segment of the iron core; L,i The equivalent current source for heating the low-voltage winding is equal to the heating power of the i-th segment of the low-voltage winding; Φ H,i The equivalent current source for heating the high-voltage winding is equal to the heating power of the i-th segment of the high-voltage winding; each resistor R xx This represents the thermal resistance along the corresponding heat flow path; the model simplifies the complex heat transfer process into a circuit network, where temperature is equivalent to node voltage and heat flow power is equivalent to the current source injected into the node (such as the iron core heat source Φ). IRON,i Low-voltage winding heat source Φ L,i High-voltage winding heat source Φ H,i The heat conduction and convection processes between components are equivalent to thermal resistance (R). xx This model is also divided into N segments along the axial direction, consistent with the finite element model and sensor arrangement. The advantage of this model is its extremely fast computation speed.

[0080] S62: Measure the top oil temperature and bottom oil temperature inside the transformer respectively, and record them as ΔT. C top , △T C bottom ;

[0081] S7. The temperature of short-circuit fault between winding turns is inverted using a thermal circuit model.

[0082] S71: Based on the overheating fault section determined by S53, the equivalent circuit method is adopted: In Figure 3 Virtual voltage sources U are introduced at nodes i, j, and k, respectively. x1 U x2 Ux3, based on Kirchhoff's laws, construct the modified nodal voltage equation system G△T=Φ, that is:

[0083]

[0084] Solving for ΔT, we get ΔT = G. -1 Φ; where each element in the vector △T is represented as a function of the variable U to be determined. x1 U x2 The linear combination expression of Ux3;

[0085] S72, Based on the verification data △T C In the temperature field distribution solution of the vector ΔT, the temperature rise components of the top oil temperature and the bottom oil temperature are located, forming the variable set ΔT to be optimized. x =[△T oil,bot , △T oil,top This leads to the optimization problem of matching oil temperature rise:

[0086] J = min||ΔT x -ΔT C ||2 (2)

[0087] S73. Based on the fault temperature rise model (2) established in S72 above, numerical solutions are obtained by using optimization algorithms (such as gradient descent, genetic algorithm or particle swarm optimization). x1 U x2 The global optimal solution for Ux3; U x1 U x2 Ux3 and Ux3 correspond to the fault temperature rise values ​​of the transformer core, low-voltage winding, and high-voltage winding, respectively, thereby enabling a quantitative assessment of the severity of transformer overheating faults.

[0088] In an optional implementation, this application can employ a more refined three-dimensional finite element model for simulation. The subsequent stages of the method, namely the online positioning stage and the online quantization stage (corresponding to steps 101 and 103), can have the same logic and algorithm as the aforementioned embodiments.

[0089] Specifically, for example, in step 101, instead of a two-dimensional axisymmetric model, this embodiment establishes a three-dimensional sector model that can more realistically reflect the three-dimensional structure and physical field distribution of the transformer. For example, for transformers with periodic structures, a 1 / 4 or 1 / 8 sector geometric model can be established, and periodic boundary conditions can be applied to the cut surface. This three-dimensional model can contain more structural details that cannot be reflected in a two-dimensional model, such as the complex oil flow at the winding ends and the influence of the outgoing line device on the surrounding temperature field.

[0090] Understandably, the computational cost (including time and computational resources) of building and solving a 3D model is much higher than that of a 2D model. However, it is important to emphasize that this high computational cost occurs entirely in the offline modeling phase and is a one-time investment. Once the fault temperature rise critical value vector ΔTc is calculated and generated based on this high-precision 3D model, the subsequent online diagnostic process still relies on efficient numerical comparison and rapid thermal circuit model inversion.

[0091] The workflow for offline simulation using a 3D sector model is similar to that of the aforementioned embodiments:

[0092] 1. Establish a three-dimensional sector geometric model and perform fine mesh generation.

[0093] 2. Perform a three-dimensional electromagnetic-fluid-temperature multiphysics coupled simulation under normal operating conditions to obtain the normal temperature rise distribution ΔT on the surface of the tank wall. norm .

[0094] 3. Apply preset faults (such as inter-turn short circuits or oil passage blockages) to each winding unit in the 3D model in sequence, and perform multiple fault condition simulations to obtain the temperature rise distribution of the box wall under each fault.

[0095] 4. Based on the simulation results of normal and fault conditions, the same logic as in the previous embodiments is used to calculate a more accurate fault temperature rise critical value vector ΔTc.

[0096] Because this set of ΔTc data originates from a model that more closely approximates physical reality, its reliability and accuracy are significantly improved. Using this set of high-precision critical values ​​in the online fault location phase makes the fault location results more reliable, reducing the probability of false positives and false negatives. Ultimately, the accuracy foundation of the entire diagnostic method is strengthened, making the final fault quantification results more credible.

[0097] Based on the description of the foregoing method and structural embodiments, this application also provides a transformer winding overheating fault diagnosis system.

[0098] Figure 4 This is a schematic diagram of a transformer winding overheating fault diagnosis system provided in an embodiment of this application. Figure 4As shown, the transformer winding overheating fault diagnosis system 400 includes:

[0099] The data generation module 410 is used to establish a temperature field model of the target transformer under normal operating conditions and various preset winding overheating fault conditions through finite element simulation method, and to calculate a set of fault temperature rise critical values ​​corresponding to the location of each winding section based on the simulation results of the temperature field model.

[0100] The fault location module 420 is used to acquire measured temperature rise data at multiple locations on the surface of the target transformer's tank when the transformer is running online, and compare the measured temperature rise data with the fault temperature rise threshold value to locate the winding section where an overheating fault has occurred.

[0101] The fault quantification module 430 is used to calculate the actual overheating temperature rise of the fault section by using a preset transformer equivalent thermal circuit model and combined with measured top and bottom oil temperature data through inversion calculation.

[0102] Optionally, the transformer winding overheat fault diagnosis system 400 also includes:

[0103] Temperature sensor array 440 is arranged along the vertical direction of the transformer tank to correspond to the position of each winding disc, so as to collect the surface temperature data of the tank in real time.

[0104] The data processing unit 450 is used to filter, normalize, and extract features from the collected temperature data.

[0105] The early warning module 460 is used to generate a graded early warning signal when the detected actual overheating temperature rise exceeds a preset threshold.

[0106] Understandably, this involves Figure 4 The relevant content of each module in the above method embodiments has been described in detail, and you can refer to the content of the method embodiments for details; that is... Figure 4 The provided transformer winding overheating fault diagnosis system 400 can perform, for example... Figure 1 Any step in the illustrated embodiment, or any step such as S1-S7, will not be described in detail here.

[0107] In one embodiment, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, causes the processor to perform any of the steps in the above method embodiments.

[0108] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0109] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0110] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for diagnosing overheating faults in transformer windings, characterized in that, include: Using the finite element simulation method, a temperature field model of the target transformer under normal operating conditions and various preset winding overheating fault conditions is established. Based on the simulation results of the temperature field model, a set of fault temperature rise critical values ​​corresponding to the location of each winding section are calculated. When the transformer is running online, the measured temperature rise data at multiple locations on the surface of the transformer tank are acquired, and the measured temperature rise data is compared with the fault temperature rise threshold to locate the winding section where the overheating fault has occurred. For the identified fault section, the actual overheating temperature rise of the fault section is calculated by using a preset transformer equivalent thermal circuit model and combined with measured top and bottom oil temperature data through inversion calculation.

2. The method for diagnosing transformer winding overheating faults according to claim 1, characterized in that, The preset winding overheating fault conditions include conditions simulating inter-turn short circuit faults or conditions simulating winding oil passage blockage faults.

3. The method for diagnosing transformer winding overheating faults according to claim 2, characterized in that, The simulated inter-turn short-circuit fault condition is achieved by increasing the excitation current of a specific winding disc to a preset range of 150% to 500% of the rated value.

4. The method for diagnosing transformer winding overheating faults according to claim 1, characterized in that, The finite element simulation method uses a two-dimensional axisymmetric model or a three-dimensional sector model for modeling. The establishment of a temperature field model of the transformer under normal operating conditions and various preset winding overheating fault conditions using the finite element simulation method specifically includes: The electromagnetic thermal coupling unit, which includes the A-phase high-voltage winding, low-voltage winding, core side column, and enclosure, is selected as the target area from the three-dimensional geometric model of the target transformer. A two-dimensional axisymmetric simplified model was established using polar coordinates, preserving the interlayer insulation and oil channel structure features of the windings, and setting material parameters and boundary conditions consistent with the actual model.

5. The method for diagnosing transformer winding overheating faults according to claim 1, characterized in that, The inversion calculation method includes: At the nodes representing the located fault sections in the equivalent thermal circuit model, virtual voltage sources are introduced to characterize unknown fault heat sources in order to construct a modified set of node voltage equations.

6. The method for diagnosing transformer winding overheating faults according to claim 5, characterized in that, The inversion calculation method also includes: An optimization problem is established based on the modified set of node voltage equations. The optimization problem aims to minimize the difference between the top oil temperature and bottom oil temperature data calculated by the model and the measured top oil temperature and bottom oil temperature data.

7. The method for diagnosing transformer winding overheating faults according to claim 6, characterized in that, The acquisition of measured temperature rise data at multiple locations on the surface of the transformer housing includes: The optimal solution of the virtual voltage source is obtained by solving the optimization problem using gradient descent or particle swarm optimization algorithm, and this optimal solution is used as the actual overheating temperature rise value of the fault section.

8. The method for diagnosing transformer winding overheating faults according to claim 1, characterized in that, The acquisition of measured temperature rise data at multiple locations on the surface of the target transformer's enclosure includes: The measured temperature rise data is obtained by using multiple temperature sensors arranged on the surface of the target transformer housing and corresponding to the positions of each winding disc along the axial direction.

9. A transformer winding overheating fault diagnosis system, characterized in that, include: The data generation module is used to establish a temperature field model of the target transformer under normal operating conditions and various preset winding overheating fault conditions through finite element simulation method, and to calculate a set of fault temperature rise critical values ​​corresponding to the location of each winding section based on the simulation results of the temperature field model. The fault location module is used to acquire measured temperature rise data at multiple locations on the surface of the target transformer's tank when the transformer is running online, and compare the measured temperature rise data with the fault temperature rise threshold value to locate the winding section where an overheating fault has occurred. The fault quantification module is used to calculate the actual overheating temperature rise of the fault section by using a preset transformer equivalent thermal circuit model and combined with measured top and bottom oil temperature data through inversion calculation.

10. The transformer winding overheating fault diagnosis system according to claim 9, characterized in that, The system also includes: A temperature sensor array is arranged along the vertical direction of the transformer tank to correspond to the position of each winding disc, so as to collect the surface temperature data of the tank in real time. The data processing unit is used to filter, normalize, and extract features from the collected temperature data. The early warning module is used to generate a graded early warning signal when the detected actual overheating temperature rise exceeds a preset threshold.

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