A method for estimating transformer winding short-circuit impulse margin based on online stress sensing and numerical calculation

Abstract

The present invention relates to a transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation, belonging to the technical field of transformers, and comprising the following steps: obtaining real-time stress distribution data of the winding during transformer operation; establishing a three-dimensional simulation numerical calculation model of transformer winding short-circuit impact deformation; dynamically correcting the transformer three-dimensional simulation numerical calculation model according to the real-time stress distribution data; evaluating the number of short-circuit impacts that the winding can withstand within the full life cycle by considering the cumulative effect according to the corrected numerical calculation model; determining the load threshold of the winding deformation according to the corrected numerical calculation model; determining the stress distribution model of the critical state of the winding deformation according to the load threshold; determining the short-circuit impact margin coefficient of the power transformer according to the real-time stress distribution data of the winding and the winding stress distribution model of the critical state of the winding deformation; and establishing an estimation model for the transformer short-circuit impact margin.

Description

Technical Field

[0001] The invention belongs to the technical field of transformers and relates to a transformer winding short-circuit impact margin estimation method combining online stress sensing with numerical calculation. Background Art

[0002] Transformers are core equipment in the power transmission process. With the continuous increase in power grid capacity, transformer damage accidents caused by short-circuit faults are on the rise. The dismantling and inspection of short-circuit damaged transformers found that the fault characteristics are mostly permanent instability deformations such as winding twisting, tilting, collapse, bulging and displacement under the action of axial force and radial force generated by fault current. The above deformations will further lead to faults such as inter-turn short circuit, inter-cake discharge and main insulation breakdown. If the transformer winding deformation can be monitored in real time by sensing means in a timely and effective manner, the probability of failure caused by transformer winding deformation can be effectively prevented and controlled, and timely maintenance measures can be taken to maintain and replace the transformer to avoid serious failures, thereby ensuring the safe and stable operation of the power system.

[0003] In recent years, the research on transformer winding deformation has mainly focused on non-electrical detection methods such as oil chromatography analysis and offline detection methods based on electrical signals such as frequency response method and short-circuit impedance method. Although the above methods can accurately determine the approximate location and degree of winding deformation, they cannot obtain the state of the transformer winding in real time, let alone the short-circuit impact margin of the transformer winding, so they cannot effectively reduce the occurrence rate of faults. In the field of transformer winding deformation monitoring, there is a lack of real-time and predictable winding short-circuit impact margin assessment model. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation, wherein the stress distribution data of the transformer winding is obtained in real time through a stress sensor, and the numerical calculation model of the transformer winding is dynamically corrected based on the online stress monitoring data to obtain the load threshold and the short-circuit impact margin coefficient that the winding structure can withstand, and the number of short-circuit impacts that the transformer winding can withstand during its entire life cycle is calculated by considering the cumulative effect of winding deformation, and finally a transformer winding short-circuit impact margin estimation model is established according to the short-circuit impact margin coefficient and the number of short-circuit impacts.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A transformer winding short-circuit impulse margin estimation method combining online stress sensing and numerical calculation comprises the following steps:

[0007] S1: Obtain real-time stress distribution data of the winding during transformer operation;

[0008] S2: Establish a three-dimensional numerical calculation model for transformer winding short-circuit impact deformation;

[0009] S3: dynamically modifying the three-dimensional simulation numerical calculation model of the transformer according to the real-time stress distribution data;

[0010] S4: Evaluate the number of short-circuit shocks that the winding can withstand within the entire life cycle by considering the cumulative effect according to the modified numerical calculation model;

[0011] S5: Determine a load threshold of winding deformation according to the modified numerical calculation model;

[0012] S6: Determine a stress distribution model of a critical state of winding deformation according to the load threshold;

[0013] S7: determining the short-circuit impact margin coefficient of the power transformer according to the real-time stress distribution data of the winding and the winding stress distribution model of the critical state of winding deformation;

[0014] S8: Establish an estimation model for transformer short-circuit impact margin.

[0015] Furthermore, in step S1, a distributed optical fiber stress sensor is used to collect stress distribution on high and low voltage windings in real time and import it into the three-dimensional simulation numerical calculation model of the transformer for parameter update and model correction.

[0016] Further, the three-dimensional simulation numerical calculation model of transformer winding short-circuit impact deformation in step S2 includes modeling windings, stays and pads, three-dimensional spatial reconstruction of the transformer body, bushings, and tap switches, and three-dimensional rendering, multi-temporal spatial data fusion, and electromagnetic-force-structure multi-physics field coupling to construct a three-dimensional coupled electromagnetic field model of the transformer, and calculate the vector magnetic potential A and magnetic flux density B:

[0017]

[0018]

[0019] Where Ω represents the electromagnetic field, z represents the z-axis of the cylindrical coordinate system, v represents the magnetic reluctance, A represents the vector magnetic potential, r represents the r-vector of the cylindrical coordinate system, and J s represents the source current density, Γ1 represents the first type of boundary condition, A0 represents the vector magnetic potential boundary value, Γ2 represents the second type of boundary condition, n represents the boundary normal, H t represents the tangential magnetic field strength, B z represents the axial component of the magnetic flux density, B r Represents the radial component of magnetic flux density;

[0020] The distribution of electromagnetic force F on the winding is obtained by finite element analysis, and the deformation of the transformer winding under the action of electromagnetic force is calculated based on the electromagnetic-force-structure coupling method:

[0021]

[0022] Among them, F r Represents the radial component of electromagnetic force, F z Represents the axial component of the electromagnetic force.

[0023] Further, in step S3, according to the real-time stress distribution data of the winding during the operation of the transformer, the winding stress parameters in the three-dimensional simulation numerical calculation model of the transformer are dynamically updated, and the numerical calculation model is subjected to reliability analysis, parameter optimization and dynamic correction by using correlation analysis. The correction steps are as follows:

[0024] Obtaining online stress distribution measured data and stress distribution data calculated by numerical calculation model;

[0025] Conduct correlation analysis on measured stress data and calculated model stress data;

[0026] If the correlation between the two is good, the numerical calculation model is considered to be a reliable model;

[0027] If the correlation between the two is not good, the stiffness, mass, and boundary constraints of the numerical calculation model are optimized and dynamically corrected to finally obtain a reliable numerical calculation model.

[0028] Further, in step S4, based on the elastic-plastic mechanics analysis principle, considering the cumulative effect of winding plastic deformation and axial and radial stability, the number of short-circuit impacts that the transformer winding can withstand during the entire life cycle is predicted, including the following steps:

[0029] S41: Calculate the deformation and electromagnetic force distribution of the winding under the short-circuit current impact and record them;

[0030] S42: Determine whether the winding deformation reaches a deformation threshold set in advance;

[0031] S43: If the winding deformation amount does not reach the threshold, the last calculation result is used as the initial state model for the next time, and the calculation is repeated;

[0032] S44: If the winding deformation reaches a threshold value, the calculation is stopped and the number of calculations is output, which is the number of short-circuit shocks that can be tolerated during the entire life cycle.

[0033] Further, in step S5, an elastic-fixed support model of the low-voltage winding and an elastic-fixed support model of the high-voltage winding, a buckling deformation analysis of the low-voltage winding and an elastic-plastic deformation analysis of the high-voltage winding are included;

[0034] The buckling deformation analysis of the low voltage winding specifically includes:

[0035] The relationship between the displacement increment of the winding structure node and the winding stress and load:

[0036] ([K]0+λ[K] δ )[Δq]=[ΔS]

[0037] Where [K]0 is the initial stiffness matrix, [K] δ is the initial stress matrix, Δq is the node displacement increment, and ΔS is the load change;

[0038] Solution of eigenvalue at critical instability:

[0039] det([K]0+λ[K] δ )=0

[0040] The characteristic value λ is multiplied by the initial load P0 to obtain the load threshold P cr ;

[0041] The high voltage winding load threshold value is specifically comprised of the following by elastic-plastic deformation analysis:

[0042] The winding struts are regarded as elastic elements and constrained to only undergo radial displacement. The change in strut support strength is simulated by changing the elastic coefficient of the spring.

[0043] Through coupling, the electromagnetic force is applied as a load to the structural field, and a finite element expression based on the incremental virtual displacement principle is established in the structural field. The finite element system equilibrium equation is obtained as follows:

[0044]

[0045] In the formula, K ep is the elastic-plastic stiffness matrix of the system, Δa is the incremental displacement phasor, and ΔQ is the unbalanced force phasor;

[0046] From the material constitutive relation, we can get:

[0047] Δε=BΔa

[0048] Where B is the strain matrix of the unit, Δε is the strain increment;

[0049] Δσ=D e Δε+∫D ep dε

[0050] Where D e is the elasticity matrix, D ep is the elastic-plastic matrix, Δσ is the stress increment;

[0051] The load-deformation response curve of the model is obtained by load scanning on the elastic support model. It is believed that the load when the deformation amount is equal to 3% is the load threshold of the high-voltage winding deformation.

[0052] Further, in step S7, the transformer short-circuit impact margin coefficient is defined:

[0053]

[0054] In the above formula, K is the margin coefficient, including the margin coefficients of high-voltage winding and low-voltage winding, σ critical is the critical stress, σ real It is the real-time stress value collected by the stress sensor.

[0055] The beneficial effect of the present invention is that the present invention provides support for reducing the probability of transformer failure and improving the safety and reliability of power system operation.

[0056] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0058] Figure 1 This is a flow chart of the transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation according to the present invention;

[0059] Figure 2 It is the elastic clamping model of low voltage winding;

[0060] Figure 3 It is the elastic support model of high voltage winding;

[0061] Figure 4 Response curves for buckling analysis;

[0062] Figure 5 Calculate the model correction flow chart for step 3;

[0063] Figure 6 Flowchart for short circuit impact number evaluation. DETAILED DESCRIPTION

[0064] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0065] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0066] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0067] The present invention proposes a transformer winding short-circuit impact margin estimation model design method combining online stress sensing and numerical calculation, and proposes a real-time evaluation method for the short-circuit impact margin of the operating power transformer winding. This method fills the gap in the previous effective evaluation method for the short-circuit impact margin of the operating power transformer winding, and uses real-time monitoring data to update and correct the calculation model parameters in real time, fundamentally improving the accuracy of the transformer winding short-circuit impact margin. In order to make the technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0068] like Figure 1 As shown, the specific steps of the method of the present invention are as follows:

[0069] 1) Collect real-time stress data of transformer windings in operation

[0070] The real-time stress data of transformer windings is acquired in real time through distributed optical fiber stress sensors. This data is imported into the three-dimensional simulation numerical calculation model of the transformer for parameter updating and model correction.

[0071] 2) Establish a three-dimensional numerical calculation model for transformer winding short-circuit impact deformation

[0072] The transformer body, bushing, and tap changer are reconstructed and rendered in three-dimensional space with high precision. The windings, stays, and pads are modeled in detail to fully simulate the actual operation of the transformer windings. The three-dimensional coupled electromagnetic field model of the transformer is constructed by field-circuit coupling, and the vector magnetic potential A and magnetic flux density B are calculated:

[0073]

[0074]

[0075] The distribution of electromagnetic force F on the winding is obtained by finite element analysis, and the deformation of the transformer winding under the action of electromagnetic force is calculated based on the electromagnetic-force-structure coupling method.

[0076]

[0077] 3) Modify the transformer 3D simulation numerical calculation model according to the real-time stress distribution data, such as Figure 5 As shown:

[0078] The online correction steps of the transformer numerical calculation model based on online stress monitoring are as follows:

[0079] Obtaining online stress distribution measured data and stress distribution data calculated by numerical calculation model;

[0080] Conduct correlation analysis on measured stress data and calculated model stress data;

[0081] If the correlation between the two is good, the numerical calculation model is considered to be a reliable model;

[0082] If the correlation between the two is not good, the stiffness, mass, boundary constraints and other parameters of the numerical calculation model are optimized and dynamically corrected to finally obtain a reliable numerical calculation model.

[0083] 4) If Figure 6 As shown in the figure, the cumulative effect is considered according to the modified numerical calculation model to evaluate the number of short-circuit shocks that the winding can withstand during its entire life cycle.

[0084] As shown in the attached figure, firstly calculate the deformation amount and electromagnetic force distribution of the winding under the short-circuit current impact and record them;

[0085] Then, it is determined whether the winding deformation reaches a deformation threshold value set in advance;

[0086] If the winding deformation does not reach the threshold, the last calculation result is used as the initial state model for the next time and the calculation is repeated;

[0087] If the winding deformation reaches the threshold, the calculation is stopped and the calculation times are output, which is the number of short-circuit shocks that can be tolerated during the entire life cycle.

[0088] 5) Determine the load threshold of winding deformation based on the modified numerical calculation model

[0089] The load threshold for determining winding deformation includes a high-voltage winding load threshold and a low-voltage winding load threshold.

[0090] The low voltage winding load threshold is obtained by the buckling analysis method: First, as shown in the attached Figure 2 As shown in the figure, a radial buckling model of a low-voltage winding combining fixed support and elastic support is established.

[0091] In the steady state, the winding has the following incremental balance equation:

[0092] ([K]0+λ[K] δ )[Δq]=[ΔS]

[0093] [K]0 is the initial stiffness matrix, [K] δ is the initial stress matrix, Δq is the node displacement increment, and ΔS is the load change. When the winding structure is in a critical instability state, a small load increase will also cause a large displacement change, that is, the load change ΔS in the equilibrium equation is ≈ 0. Therefore, the eigenvalue λ at instability can be obtained according to the following formula:

[0094] det([K]0+λ[K] δ )=0

[0095] The critical buckling load, or load threshold P, can be obtained by multiplying the eigenvalue λ by the initial load P0. cr The load threshold points obtained by buckling analysis of the embodiment are shown in the attached Figure 4 shown.

[0096] The high-voltage winding load threshold is obtained by elastic-plastic deformation analysis:

[0097] As attached Figure 3 The elastic support model of radial deformation of high-voltage winding is established as shown in the figure. The winding support bar is regarded as an elastic element and constrained to only undergo radial displacement. By changing the elastic coefficient of the spring, the change of the support strength of the support bar can be simulated.

[0098] Through coupling, the aforementioned electromagnetic force is loaded into the structural field as a load, and a finite element expression based on the incremental virtual displacement principle is established in the structural field, and the finite element system equilibrium equation is obtained as follows:

[0099]

[0100] In the formula, K ep is the elastic-plastic stiffness matrix of the system, Δa is the incremental displacement phasor, and ΔQ is the unbalanced force phasor.

[0101] According to the material constitutive relation, we can get:

[0102] Δε=BΔa

[0103] Where B is the strain matrix of the unit and Δε is the strain increment.

[0104] Δσ=D e Δε+∫D ep dε

[0105] Where, D e is the elasticity matrix, D ep is the elastic-plastic matrix, Δσ is the stress increment.

[0106] The load-deformation response curve of the model is obtained by load scanning on the elastic support model. It is considered that the load when the deformation is equal to 3% is the load threshold of high-voltage winding deformation.

[0107] 6) Determine the stress distribution model of the critical state of winding deformation based on the load threshold

[0108] The stress distribution model of the transformer winding in the critical instability state in the numerical calculation model is obtained by performing load scanning by specifying the displacement.

[0109] 7) Determine the short-circuit impact margin of the power transformer based on the real-time stress data of the winding in the transformer entity and the winding stress distribution of the critical state of winding deformation in the calculation model

[0110] In order to characterize the size of the short-circuit impact margin, the concept of short-circuit impact margin coefficient is proposed, as shown in the following formula:

[0111]

[0112] In the above formula, K is the margin coefficient, including the margin coefficients of high-voltage winding and low-voltage winding. critical is the critical stress, σ real It is the real-time stress value collected by the stress sensor.

[0113] 8) Establish a prediction model for transformer short-circuit impact margin based on the number of short-circuit impacts that can be tolerated during the entire life cycle and the short-circuit impact margin coefficient

[0114] The greater the number of short-circuit shocks that the transformer can withstand during its entire life cycle, the stronger the transformer's ability to resist short-circuit shocks and the higher the transformer's short-circuit shock margin.

[0115] The larger the short-circuit impact margin coefficient of the transformer, the higher the risk probability of winding damage when a short-circuit fault occurs, and the more urgent the need to improve and transform the transformer's short-circuit resistance.

[0116] By combining the number of short-circuit shocks that the transformer can withstand during its entire life cycle and the short-circuit shock margin coefficient, the short-circuit shock margin of the transformer can be estimated, and the operation and maintenance of the transformer can be arranged scientifically and reasonably, thereby reducing the probability of transformer failure and improving power supply reliability.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for estimating transformer winding short-circuit impact margin by combining online stress sensing and numerical calculation, characterized in that: The following steps are involved: S1: Obtain real-time stress distribution data of the winding during transformer operation; S2: Establish a three-dimensional numerical calculation model for transformer winding short-circuit impact deformation; S3: dynamically modifying the three-dimensional simulation numerical calculation model of the transformer according to the real-time stress distribution data; S4: Evaluate the number of short-circuit shocks that the winding can withstand within the entire life cycle by considering the cumulative effect according to the modified numerical calculation model; S5: Determine the load threshold of winding deformation according to the modified numerical calculation model; Step S5 includes an elastic support model of the low-voltage winding and an elastic support model of the high-voltage winding, a buckling deformation analysis of the low-voltage winding and an elastic-plastic deformation analysis of the high-voltage winding; The buckling deformation analysis of the low voltage winding specifically includes: The relationship between the displacement increment of the winding structure node and the winding stress and load: ([K]0+λ[K] δ )[Δq]=[ΔS] Where [K]0 is the initial stiffness matrix, [K] δ is the initial stress matrix, Δq is the node displacement increment, and ΔS is the load change; Solution of eigenvalue at critical instability: det([K]0+λ[K] δ )=0 The characteristic value λ is multiplied by the initial load P0 to obtain the load threshold P cr ; The high voltage winding load threshold value is specifically comprised of the following by elastic-plastic deformation analysis: The winding struts are regarded as elastic elements and constrained to only undergo radial displacement. The change in strut support strength is simulated by changing the elastic coefficient of the spring. Through coupling, the electromagnetic force is loaded into the structural field as a load, and a finite element expression based on the incremental virtual displacement principle is established in the structural field, and the finite element system equilibrium equation is obtained as follows: In the formula, K ep is the elastic-plastic stiffness matrix of the system, Δa is the incremental displacement phasor, and ΔQ is the unbalanced force phasor; From the material constitutive relation, we can get: Δε=BΔa Where B is the strain matrix of the unit, Δε is the strain increment; Δσ=D e De+∫D ep d Where D e is the elasticity matrix, D ep is the elastic-plastic matrix, Δσ is the stress increment; The load-deformation response curve of the model is obtained by load scanning on the elastic support model. It is considered that the load when the deformation is equal to 3% is the load threshold of high-voltage winding deformation. S6: Determine a stress distribution model of a critical state of winding deformation according to the load threshold; S7: Determine the short-circuit impact margin coefficient of the power transformer according to the real-time stress distribution data of the winding and the winding stress distribution model of the critical state of winding deformation; define the short-circuit impact margin coefficient of the transformer: In the above formula, K is the margin coefficient, including the margin coefficients of high-voltage winding and low-voltage winding, σ critical is the critical stress, σ real It is the real-time stress value collected by the stress sensor; S8: Establish an estimation model for transformer short-circuit impact margin.

2. The transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation according to claim 1 is characterized in that: In step S1, a distributed optical fiber stress sensor is used to collect stress distribution on high and low voltage windings in real time and import it into a three-dimensional simulation numerical calculation model of the transformer for parameter update and model correction.

3. The transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation according to claim 1 is characterized in that: The three-dimensional simulation numerical calculation model of transformer winding short-circuit impact deformation in step S2 includes modeling windings, stays and pads, three-dimensional spatial reconstruction of the transformer body, bushings, and tap switches, and three-dimensional rendering, multi-temporal spatial data fusion, and electromagnetic-force-structure multi-physics field coupling to construct a three-dimensional coupled electromagnetic field model of the transformer and calculate the vector magnetic potential A and magnetic flux density B: Where Ω represents the electromagnetic field, z represents the z-axis of the cylindrical coordinate system, v represents the magnetic reluctance, A represents the vector magnetic potential, r represents the r-vector of the cylindrical coordinate system, and J s represents the source current density, Γ1 represents the first type of boundary condition, A0 represents the vector magnetic potential boundary value, Γ2 represents the second type of boundary condition, n represents the boundary normal, H t represents the tangential magnetic field strength, B z represents the axial component of the magnetic flux density, B r Represents the radial component of magnetic flux density; The distribution of electromagnetic force F on the winding is obtained by finite element analysis, and the deformation of the transformer winding under the action of electromagnetic force is calculated based on the electromagnetic-force-structure coupling method: Among them, F r Represents the radial component of electromagnetic force, F z Represents the axial component of the electromagnetic force.

4. The transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation according to claim 1 is characterized in that: In step S3, according to the real-time stress distribution data of the winding during the operation of the transformer, the winding stress parameters in the three-dimensional simulation numerical calculation model of the transformer are dynamically updated, and the numerical calculation model is subjected to reliability analysis, parameter optimization and dynamic correction by using correlation analysis. The correction steps are as follows: Obtaining online stress distribution measured data and stress distribution data calculated by numerical calculation model; Conduct correlation analysis on measured stress data and calculated model stress data; If the correlation between the two is good, the numerical calculation model is considered to be a reliable model; If the correlation between the two is not good, the stiffness, mass, and boundary constraints of the numerical calculation model are optimized and dynamically corrected to finally obtain a reliable numerical calculation model.

5. The transformer winding short-circuit impact margin estimation method combining online stress sensing and numerical calculation according to claim 1 is characterized in that: In step S4, based on the principle of elastic-plastic mechanics analysis, considering the cumulative effect of winding plastic deformation and axial and radial stability, the number of short-circuit impacts that the transformer winding can withstand during the entire life cycle is predicted, including the following steps: S41: Calculate the deformation and electromagnetic force distribution of the winding under the short-circuit current impact and record them; S42: Determine whether the winding deformation reaches a deformation threshold set in advance; S43: If the winding deformation amount does not reach the threshold, the last calculation result is used as the initial state model for the next time, and the calculation is repeated; S44: If the winding deformation reaches a threshold value, the calculation is stopped and the number of calculations is output, which is the number of short-circuit shocks that can be tolerated during the entire life cycle.

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