Transformer winding deformation monitoring method, device and system

Abstract

The invention relates to the technical field of electrical variable measurement, in particular to a transformer winding deformation monitoring method, device and system, design parameters of a transformer are obtained, working parameters of the transformer are obtained in the operation process of the transformer, and the operation process of the transformer comprises normal circuit operation and multiple times of circuit short circuit. According to the design parameters and the working parameters, the affected strength coefficient of the transformer winding when the circuit is short-circuited each time is determined, the influence on the transformer winding is considered, and the accuracy of a subsequent deformation monitoring result is improved; determining a theoretical working parameter range corresponding to the transformer winding after each time of short circuit according to the affected strength coefficient and the working parameter, and determining the real deformation possibility of the transformer winding after each time of short circuit according to the theoretical working parameter range and the working parameter. The deformation monitoring result of the transformer winding is determined according to the real deformation possibility and the possibility threshold, the process is simple, and the deformation monitoring efficiency is high.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring electrical variables, and in particular to a method, device and system for monitoring deformation of a transformer winding. Background Art

[0002] A transformer is an electrical device that works based on the principle of electromagnetic induction, mainly used to change the voltage and current of alternating current while keeping the basic power of power transmission unchanged. A transformer usually consists of two core components, an iron core and a winding (coil), and the winding is the core component of the transformer, and its design directly affects voltage conversion, efficiency and heat dissipation performance. However, during the operation of the transformer, it is inevitably subjected to the impact of various short-circuit fault currents. When a short-circuit occurs, the temperature of the winding rises, the mechanical strength decreases, and the electrodynamic force will cause the winding to be more easily damaged or deformed.

[0003] Currently, the deformation monitoring of the transformer winding mainly relies on the vibration signals that may exist during the deformation of the winding and the changes in the electrical parameters of the transformer caused by the deformation of the winding. When obvious data changes occur, it is considered that the winding of the transformer is deformed, and then off-line detection and other operations are carried out. However, the changes in the vibration data and electrical parameters of the transformer may also be caused by other factors, such as insulation aging, external short circuits and external vibrations. Therefore, if it is necessary to determine the winding deformation, it is necessary to check one by one, which is very cumbersome, resulting in a low detection efficiency of the winding deformation. At the same time, due to the many factors causing data changes, the detection accuracy of the winding deformation is low. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method, device and system for monitoring deformation of a transformer winding, and the specific technical solutions adopted are as follows: In the first aspect, an embodiment of the present application provides a method for monitoring deformation of a transformer winding, including: Obtain the design parameters of the transformer, and during the operation of the transformer, obtain the working parameters of the transformer. The operation process of the transformer includes normal circuit operation and several circuit short circuits; According to the design parameters and the working parameters, determine the influence intensity coefficient of the transformer winding during each circuit short circuit; According to the influence intensity coefficient and the working parameters, determine the theoretical working parameter range corresponding to the transformer winding after each circuit short circuit; According to the theoretical working parameter range and the working parameters, determine the real deformation possibility of the transformer winding after each circuit short circuit, and according to the real deformation possibility and the possibility threshold, determine the deformation monitoring result of the transformer winding.

[0005] In one embodiment, the design parameters include the length of the winding conductor and the total mass of the transformer winding and the iron core, and the operating parameters include parameters of several data dimensions, including the input current, output current, vibration amplitude, vibration frequency of the transformer, and the temperature of the transformer winding; determining the influence intensity coefficient of the transformer winding during each short circuit according to the design parameters and the operating parameters includes: Determine the short-circuit current value of the transformer during each short circuit according to the input current and the output current during each short circuit, respectively; Determine the electromagnetic force received by the transformer winding during each short circuit according to the short-circuit current value and the length of the winding conductor, respectively; Determine the electromagnetic force influence coefficient during each short circuit according to the vibration amplitude, vibration frequency, electromagnetic force received by the transformer winding during short circuit, and the total mass during each short circuit, respectively; Determine the average short-circuit temperature during each short circuit according to the temperature of the transformer winding, and determine the influence intensity coefficient of the transformer winding during each short circuit according to the average short-circuit temperature, the electromagnetic force influence coefficient, and the time length of the short circuit, respectively.

[0006] In one embodiment, determining the influence intensity coefficient of the transformer winding during each short circuit according to the average short-circuit temperature, the electromagnetic force influence coefficient, and the time length of the short circuit includes: Determine the first product of the average short-circuit temperature, the electromagnetic force influence coefficient, and the time length, respectively; Determine the influence intensity coefficient of the transformer winding during each short circuit according to the first product and the normalization function, respectively.

[0007] In one embodiment, determining the theoretical operating parameter range corresponding to the transformer winding after each short circuit according to the influence intensity coefficient and the operating parameters includes: Determine the first time interval between two adjacent short circuits and the second time interval between two short circuits according to the operating parameters, and determine the attenuation weight of the transformer winding during each short circuit according to the first time interval, respectively; Determine the working parameter attenuation influence coefficient corresponding to between two short circuits according to the attenuation weight of the transformer winding during each short circuit, the influence intensity coefficient of the transformer winding during each short circuit, and the second time interval; Determine the working parameter interval attenuation coefficient of the transformer winding during each short circuit according to each working parameter attenuation influence coefficient and the normalization function; Determine the original upper limit and the original lower limit of the operating parameters during normal circuit operation between two adjacent circuit short - circuits respectively. Then, determine the theoretical operating parameter range corresponding to the transformer winding after each circuit short - circuit respectively according to the original upper limit, the original lower limit, and the operating parameter interval attenuation coefficient. Among them, the original upper limit of the operating parameters includes the original upper limits corresponding to the parameters of several data dimensions respectively, and the original lower limit of the operating parameters includes the original lower limits corresponding to the parameters of several data dimensions respectively.

[0008] In one implementation manner, the step of determining the theoretical operating parameter range corresponding to the transformer winding after each circuit short - circuit according to the original upper limit, the original lower limit, and the operating parameter interval attenuation coefficient includes: Select the circuit short - circuit of the first candidate number from several circuit short - circuits, and determine the previous circuit short - circuit of the circuit short - circuit of the first candidate number as the circuit short - circuit of the second candidate number. Determine the difference between the preset value and the operating parameter interval attenuation coefficient of the circuit short - circuit of the first candidate number. According to the difference and the second product of the original upper limit of the operating parameters during normal circuit operation between the first candidate number and the second candidate number, determine the new original upper limit corresponding to the circuit short - circuit of the first candidate number, which is used as the upper limit of the theoretical operating parameters corresponding to the transformer winding after the circuit short - circuit of the second candidate number. Determine the sum of the preset value and the operating parameter interval attenuation coefficient of the circuit short - circuit of the first candidate number. According to the sum and the third product of the original lower limit of the operating parameters during normal circuit operation between the first candidate number and the second candidate number, determine the new original lower limit corresponding to the circuit short - circuit of the first candidate number, which is used as the lower limit of the theoretical operating parameters corresponding to the transformer winding after the circuit short - circuit of the second candidate number. According to the upper limit and the lower limit of the theoretical operating parameters, determine the theoretical operating parameter range corresponding to the transformer winding after the circuit short - circuit of the second candidate number. Return to the step of selecting the circuit short - circuit of the first candidate number from several circuit short - circuits until the theoretical operating parameter range corresponding to the transformer winding after each circuit short - circuit is determined.

[0009] In one implementation manner, the step of determining the true deformation possibility of the transformer winding after each circuit short - circuit according to the theoretical operating parameter range and the operating parameters includes: Select the circuit short - circuit of the first candidate number from several circuit short - circuits, and determine the previous circuit short - circuit of the circuit short - circuit of the first candidate number as the circuit short - circuit of the second candidate number. After determining the first candidate number of circuit short - circuit recoveries according to the working parameters, determine the first target working parameters when the circuit is operating normally and the second target working parameters when the circuit is operating normally after the second candidate number of circuit short - circuit recoveries, and respectively determine the first data change trend of the parameters of each data dimension during the circuit short - circuit of the first candidate number and the parameters of each data dimension in the first target working parameters, and respectively determine the second data change trend of the parameters of each data dimension during the circuit short - circuit of the second candidate number and the parameters of each data dimension in the second target working parameters; Respectively determine the parameter recovery differences corresponding to each data dimension during each circuit short - circuit according to the differences between the first data change trend of the parameters of each data dimension and the second data change trend of the parameters of each data dimension and the normalization function; According to the working parameters and the theoretical working parameter range, determine the deformation possibility of the transformer winding reflected by each data dimension after each circuit short - circuit; According to the parameter recovery differences corresponding to each data dimension after each circuit short - circuit and the deformation possibility of the transformer winding reflected by each data dimension during each circuit short - circuit, determine the true deformation possibility of the transformer winding after each circuit short - circuit.

[0010] In one implementation manner, the determining the deformation possibility of the transformer winding reflected by each data dimension after each circuit short - circuit according to the working parameters and the theoretical working parameter range includes: Compare each parameter of each data dimension in the working parameters after each circuit short - circuit recovery with the theoretical working parameter range of the corresponding data dimension one by one; When the parameter of any one data dimension in the working parameters is greater than the upper limit of the theoretical working parameters of the corresponding data dimension's theoretical working parameter range, determine the first absolute value of the difference between the parameter of this data dimension and the upper limit of the corresponding theoretical working parameters, and determine the deformation possibility of the transformer winding reflected by this data dimension after the corresponding number of circuit short - circuits according to the normalization function and the first absolute value; When the parameter of any one data dimension in the working parameters is less than the lower limit of the theoretical working parameters of the corresponding data dimension's theoretical working parameter range, determine the second absolute value of the difference between the parameter of this data dimension and the lower limit of the corresponding theoretical working parameters, and determine the deformation possibility of the transformer winding reflected by this data dimension after the corresponding number of circuit short - circuits according to the normalization function and the second absolute value.

[0011] In one implementation manner, the determining the true deformation possibility of the transformer winding after each circuit short - circuit according to the parameter recovery differences corresponding to each data dimension after each circuit short - circuit and the deformation possibility of the transformer winding reflected by each data dimension during each circuit short - circuit includes: Determine the start time of each short circuit of the circuit, respectively determine the start time and the recovery time of the normal operation of the circuit after the corresponding number of short circuits of the circuit are restored, and respectively determine the elapsed time from the start time to the recovery time; Respectively determine the data anomaly tolerance corresponding to each data dimension after each short circuit of the circuit according to the elapsed time and the parameter recovery difference; Respectively determine the reciprocal of the data anomaly tolerance corresponding to each data dimension after each short circuit of the circuit, the preset weight, and the fourth product of the deformation possibility of the transformer winding reflected by each data dimension after each short circuit of the circuit; Perform summation averaging according to the fourth product and the number of dimensions of the data dimension, and determine the true deformation possibility of the transformer winding after each short circuit of the circuit according to the summation averaging result and the normalization function.

[0012] In a second aspect, an embodiment of the present application provides a transformer winding deformation monitoring system, including: An acquisition module, configured to acquire the design parameters of the transformer and, during the operation of the transformer, acquire the working parameters of the transformer, where the operation process of the transformer includes normal operation of the circuit and several short circuits of the circuit; A first determination module, configured to determine the influence intensity coefficient of the transformer winding at the time of each short circuit of the circuit according to the design parameters and the working parameters; A second determination module, configured to determine the theoretical working parameter range corresponding to the transformer winding after each short circuit of the circuit according to the influence intensity coefficient and the working parameters; A monitoring module, configured to determine the true deformation possibility of the transformer winding after each short circuit of the circuit according to the theoretical working parameter range and the working parameters, and determine the deformation monitoring result of the transformer winding according to the true deformation possibility and the possibility threshold.

[0013] In a third aspect, an embodiment of the present application provides a transformer winding deformation monitoring device, including: a processor and a memory, where instructions are stored in the memory, and the instructions are loaded and executed by the processor to implement the method in any one of the above aspects.

[0014] The present invention has the following beneficial effects: By obtaining the design parameters of the transformer and, during the operation of the transformer, obtaining the operating parameters, where the operation process of the transformer includes normal circuit operation and several circuit short - circuits, according to the design parameters and the operating parameters, determine the influence intensity coefficient of the transformer winding during each circuit short - circuit, considering the influence on the transformer winding, improve the accuracy of the subsequent determined deformation monitoring results; according to the influence intensity coefficient and the operating parameters, determine the theoretical operating parameter range corresponding to the transformer winding after each circuit short - circuit, according to the theoretical operating parameter range and the operating parameters, determine the true deformation possibility of the transformer winding after each circuit short - circuit, and according to the true deformation possibility and the possibility threshold, determine the deformation monitoring result of the transformer winding. The deformation monitoring process is simple and improves the deformation monitoring efficiency of the transformer winding. Brief Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a schematic flowchart of the steps of a method for monitoring the deformation of a transformer winding provided by an embodiment of the present invention; Figure 2 It is a structural block diagram of a system for monitoring the deformation of a transformer winding provided by an embodiment of the present invention; Figure 3 It is a structural block diagram of a device for monitoring the deformation of a transformer winding provided by an embodiment of the present invention. Detailed Embodiments

[0017] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific embodiments, structures, features, and their effects of a method, device, and system for monitoring the deformation of a transformer winding proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0019] It should be noted that the "exemplary" in the embodiments of the present application refers to examples listed for convenience of description, and other embodiments are not limited to the listed examples.

[0020] The following specifically describes the specific solutions of a transformer winding deformation monitoring method, device and system provided by the present invention with reference to the accompanying drawings.

[0021] In the related art, the analysis method for the winding deformation after multiple short circuits mainly relies on the changes in the inductance and capacitance data of the transformer before and after multiple short circuits, so as to obtain the cumulative amount of winding deformation, without considering factors such as high temperature (caused by large current) and vibration (electrodynamic impact) accompanied by the winding deformation, resulting in a low credibility of the analysis result. At the same time, since transient analysis and iterative analysis of historical data are required and a simulation model needs to be constructed, it takes a certain amount of time and computing resources, and it is difficult to obtain real-time winding deformation information during the normal operation of the transformer, resulting in a high delay in the result.

[0022] Please refer to Figure 1 , which shows a flowchart of a transformer winding deformation monitoring method provided by an embodiment of the present invention. The transformer winding deformation monitoring method may at least include steps S100 - S400: S100. Obtain the design parameters of the transformer, and during the operation of the transformer, obtain the working parameters of the transformer. The operation process of the transformer includes normal circuit operation and several circuit short circuits.

[0023] S200. Determine the influence intensity coefficient of the transformer winding during each circuit short circuit according to the design parameters and the working parameters.

[0024] S300. Determine the theoretical working parameter range corresponding to the transformer winding after each circuit short circuit according to the influence intensity coefficient and the working parameters.

[0025] S400. Determine the true deformation possibility of the transformer winding after each circuit short circuit according to the theoretical working parameter range and the working parameters, and determine the deformation monitoring result of the transformer winding according to the true deformation possibility and the possibility threshold.

[0026] The technical solution of the embodiment of the present application obtains the design parameters of the transformer and, during the operation of the transformer, obtains the working parameters of the transformer. The operation process of the transformer includes normal circuit operation and several circuit short circuits. According to the design parameters and the working parameters, the influence intensity coefficient of the transformer winding during each circuit short circuit is determined, taking into account the influence on the transformer winding, thereby improving the accuracy of the subsequent determined deformation monitoring result. According to the influence intensity coefficient and the working parameters, the theoretical working parameter range corresponding to the transformer winding after each circuit short circuit is determined. According to the theoretical working parameter range and the working parameters, the true deformation possibility of the transformer winding after each circuit short circuit is determined, and according to the true deformation possibility and the possibility threshold, the deformation monitoring result of the transformer winding is determined. The deformation monitoring process is simple, improving the deformation monitoring efficiency of the transformer winding.

[0027] In one implementation, the design parameters of the transformer include, but are not limited to, the length of the winding conductor , the total mass of the transformer winding and the iron core and the proportionality constant of the transformer winding . Or, in another implementation, the design parameters of the transformer may include the total length of the transformer winding in the axial direction of the transformer iron core , the total length of the winding in the radial direction of the transformer iron core and the number of winding turns . Then, the length of the winding conductor is calculated based on the formula : , without specific limitation.

[0028] In one embodiment, the transformer is connected to the circuit so that the transformer is in an operating state. Then, during the operation of the transformer, the operating parameters of the transformer are obtained by a detection element within a certain period of time (which can be set based on actual conditions). Among them, since the operating parameters of the transformer are continuously obtained within a certain period of time, during the operation of the transformer, there may be situations where the circuit operates normally and several cases of circuit short - circuits occur. That is to say, the obtained operating parameters include partial operating parameters in the case of normal circuit operation and partial operating parameters in each case of circuit short - circuit. It should be noted that the detection element includes, but is not limited to, current sensors, voltage sensors, vibration sensors, infrared sensors, etc. In other embodiments, the types of sensors can be increased or decreased based on actual needs, and no specific limitation is made. In the embodiments of the present application, the current sensor is installed at the input end and the output end of the transformer, the voltage sensor is installed at the output end of the transformer, the vibration sensors are respectively installed on the transformer core base and the transformer housing, and the infrared sensor is installed inside the transformer. Therefore, the operating parameters can include parameters in several data dimensions, such as, but not limited to, the input - end current of the transformer, the output - end current, the output - end voltage, the vibration amplitude, the vibration frequency, and the temperature of the transformer winding. Taking the acquisition frequency of each sensor as 1 time per second as an example, when each sensor acquires the corresponding parameter, the corresponding moment will be recorded, that is, the operating parameters also include the acquisition moment corresponding to each parameter. In the embodiments of the present application, all the acquired operating parameters will be uploaded to the remote monitoring platform. Therefore, based on the analysis of the operating parameters, the remote monitoring platform can determine which times the circuit operates normally and which times which circuit short - circuit occurs (such as the start moment and the end moment of each circuit short - circuit, and the end moment is also equivalent to the recovery moment when the circuit operates normally after the recovery of the current circuit short - circuit), which is convenient for distinguishing the parameter segments corresponding to normal circuit operation and several circuit short - circuits, and which specific operating parameters are included in the corresponding parameter segments. In addition, the remote monitoring platform can perform pre - processing such as data cleaning and supplementation to ensure the accuracy of subsequent data processing.

[0029] It should be noted that when a short - circuit occurs in the circuit where the transformer is located, the magnitude of the current passing through the transformer changes, that is, the original normal current becomes a short - circuit current (large current). At this time, the remote monitoring platform can determine that a circuit short - circuit has occurred. Affected by the change in the magnitude of the current, the transformer winding will be affected by the electromagnetic force. The greater the current passing through the transformer in the circuit, the greater the electromagnetic force on the transformer winding. The greater the electromagnetic force on the winding, the greater the influence intensity coefficient of the transformer winding. Therefore, it is necessary to analyze the influence intensity coefficient of the transformer winding.

[0030] In one embodiment, step S200 includes steps S201 - S204: S201. Determine the short - circuit current value of the transformer during each circuit short - circuit respectively according to the input - end current and the output - end current during each circuit short - circuit.

[0031] Optionally, determine the input - end current during each circuit short - circuit from the operating parameters and the output - end current , then calculate the average value of the input - end current and the output - end current as the short - circuit current value of the corresponding transformer during each circuit short - circuit , that is, the short - circuit current of the transformer during the th circuit short - circuit.

[0032] S202. Determine the electromagnetic force received by the transformer winding during each circuit short - circuit respectively according to the short - circuit current value and the winding conductor length .

[0033] The specific calculation formula is: where is the electromagnetic force received by the transformer winding during the th circuit short - circuit, is the proportionality constant of the transformer winding, which can be obtained by querying the factory parameters of the transformer.

[0034] S203. Determine the electro - magnetic force influence coefficient during each circuit short - circuit respectively according to the vibration amplitude, vibration frequency, electromagnetic force received by the transformer winding during short - circuit and the total mass during each circuit short - circuit.

[0035] The specific calculation formula is: where represents the electro - magnetic force influence coefficient during the th circuit short - circuit, represents the total mass of the transformer winding and the iron core, represents the vibration amplitude of the transformer winding during the th circuit short - circuit, represents the vibration frequency of the transformer winding during the th circuit short - circuit, represents the vibration intensity of the transformer winding provided by the electro - magnetic force during the th circuit short - circuit, represents the monitored vibration intensity of the transformer winding during the th circuit short - circuit, is the normalization function. It should be noted that when the electro - magnetic force influence coefficient The smaller it is, the stronger the anti-vibration ability of the transformer winding, and the lower the intensity affected by the short circuit of the circuit. On the contrary, the electrodynamic force influence coefficient is higher, and it is more likely to be affected by the large current of the short circuit of the circuit.

[0036] S204. Determine the average short-circuit temperature during each circuit short circuit according to the temperature of the transformer winding, and respectively determine the influence intensity coefficient of the transformer winding during each circuit short circuit according to the average short-circuit temperature, the electrodynamic force influence coefficient, and the time length of the circuit short circuit.

[0037] It should be noted that since a large current appears in the circuit due to the circuit short circuit, during the operation of the transformer, the temperature of the transformer winding will rise. Furthermore, due to the higher temperature, the mechanical strength of the transformer winding is reduced. The higher the temperature during the short circuit and the longer the time of bearing the high temperature, the greater the influence intensity coefficient of the transformer winding. Therefore, the factor of temperature needs to be considered.

[0038] Optionally, determine the average short-circuit temperature during each circuit short circuit according to the temperature of the transformer winding, that is, respectively within the time length (that is, the duration during the th circuit short circuit), calculate the ratio of the sum of the temperatures of the transformer winding at all times to the number of temperatures, and determine the average short-circuit temperature during each circuit short circuit , that is, the average short-circuit temperature during the th circuit short circuit.

[0039] In an implementation manner, respectively determine the influence intensity coefficient of the transformer winding during each circuit short circuit according to the average short-circuit temperature, the electrodynamic force influence coefficient, and the time length of the circuit short circuit. Specifically: First, respectively determine the average short-circuit temperature , the electrodynamic force influence coefficient , and the time length of the first product .

[0040] Secondly, respectively determine the influence intensity coefficient of the transformer winding during each circuit short circuit according to the first product and the normalization function . The formula is: where is the influence intensity coefficient of the transformer winding during the th circuit short circuit.

[0041] It should be noted that the circuit may experience repeated short - circuit phenomena due to certain reasons, which may cause the transformer to also experience multiple short - circuits. Moreover, the more times the transformer experiences short - circuits, the mechanical strength of the transformer winding will gradually decrease due to multiple impacts, and the decrease amplitude increases gradually each time. The probability of deformation of the transformer winding is usually greater. Therefore, when predicting the theoretical working parameter range, the corresponding range is smaller.

[0042] In one embodiment, step S300 includes steps S301 - S304: S301. According to the working parameters, determine the first time interval between two adjacent circuit short - circuits and the second time interval between two - by - two circuit short - circuits, and respectively determine the attenuation weight of the transformer winding at each circuit short - circuit according to the first time interval.

[0043] Optionally, according to the working parameters at each circuit short - circuit, determine the first time interval between two adjacent circuit short - circuits. For example, the th circuit short - circuit and the -1th circuit short - circuit's first time interval , for example, after the 1st circuit short - circuit, the circuit operates normally for 60s, and then the 2nd circuit short - circuit occurs. At this time =2, then at this time is 60s, and the second time interval between two - by - two circuit short - circuits, for example, the th circuit short - circuit and the th circuit short - circuit's time interval is recorded as the second time interval. Then, respectively determine the attenuation weight of the transformer winding at each circuit short - circuit according to the first time interval: Among them, is the attenuation weight of the transformer winding at the th circuit short - circuit, when it is the 1st circuit short - circuit, the attenuation weight of the transformer winding is preset to 0; when the attenuation weight is larger, it means that the interval between two adjacent circuit short - circuits is closer, and the attenuation of the transformer winding is stronger. The shorter the interval, the more residual stress remains inside the transformer winding. At this time, when it is impacted again, the loss of the transformer winding is stronger, and the attenuation weight is larger. On the contrary, if the interval time between two adjacent circuit short - circuits is farther, the winding recovery effect is better, and the loss when impacted again is relatively lower, and the attenuation weight is smaller.

[0044] S302. Determine the attenuation influence coefficient of the working parameters corresponding to each pair of circuit short - circuits based on the attenuation weight of the transformer winding during each circuit short - circuit, the influence intensity coefficient of the transformer winding during each circuit short - circuit, and the second time interval.

[0045] Optionally, based on the attenuation weight of the transformer winding during each circuit short - circuit (e.g., the attenuation weight of the transformer winding during the th circuit short - circuit ), the influence intensity coefficient of the transformer winding during each circuit short - circuit (the influence intensity coefficient of the transformer winding during the th circuit short - circuit ), and the second time interval , determine the attenuation influence coefficient of the working parameters corresponding to each pair of circuit short - circuits . The higher this value, the stronger the influence and the greater the attenuation of the transformer winding.

[0046] S303. Determine the interval attenuation coefficient of the working parameters of the transformer winding during each circuit short - circuit based on each attenuation influence coefficient of the working parameters and the normalization function.

[0047] Specifically, the calculation formula is: Among them, when summing in the above formula, ranges from 1 to , takes values from 2 to U (U is the total number of circuit short - circuits), is the normalization function, is the interval attenuation coefficient of the working parameters of the transformer winding during the th circuit short - circuit. This interval attenuation coefficient of the working parameters represents the strength of the influence, not the direction of the influence.

[0048] S304. Respectively determine the original upper limit and the original lower limit of the working parameters during normal circuit operation between each pair of adjacent circuit short - circuits. Respectively, based on the original upper limit, the original lower limit, and the interval attenuation coefficient of the working parameters, determine the theoretical working parameter range corresponding to the transformer winding after each circuit short - circuit.

[0049] Optionally, since the working parameters include several data dimensions, the original upper limit of the working parameters includes the original upper limits corresponding to the parameters of several data dimensions respectively, and the original lower limit of the working parameters includes the original lower limits corresponding to the parameters of several data dimensions respectively; taking the two data dimensions of vibration amplitude and vibration frequency as an example, when determining the original upper limit and the original upper limit, it will respectively include the original upper limit and the original lower limit of the vibration amplitude, and also include the original upper limit and the original lower limit of the vibration amplitude. It can be understood that the finally determined theoretical working parameter range will also include the theoretical working parameter range of the vibration amplitude and the theoretical working parameter range of the vibration frequency. The same applies to other data dimensions and will not be elaborated here.

[0050] In the embodiments of the present application, the original upper limit and the original lower limit of the working parameters during the normal operation of the circuit between two adjacent circuit short - circuits are determined respectively. For example, the original upper limit and the original lower limit of the working parameters during the normal operation of the circuit between the th circuit short - circuit and the -1th circuit short - circuit are determined respectively. And the original lower limit . Suppose that the 3rd circuit short - circuit occurs 60 s after the 2nd circuit short - circuit. Then the normal operation time between these two circuit short - circuits is 60 s. Taking the two data dimensions of vibration amplitude and vibration frequency as an example, within this 60 s, the maximum value of the vibration amplitude is A, the minimum value is B, the maximum value of the vibration frequency is C, and the minimum value is D. Then it can be determined that the original upper limit of the vibration amplitude during the normal operation time between these two short - circuits is A, the original lower limit is B, the original upper limit of the vibration frequency is C, and the original lower limit is D. Therefore, finally, the original upper limits and the original lower limits of the parameters of each data dimension in the working parameters during the normal operation of the circuit between two adjacent circuit short - circuits can be determined.

[0051] In one implementation, the theoretical working parameter range corresponding to the transformer winding after each circuit short - circuit is determined respectively according to the original upper limit, the original lower limit, and the working parameter interval attenuation coefficient. Specifically: First, select the circuit short - circuit of the first candidate number from several circuit short - circuits, and determine the previous circuit short - circuit of the circuit short - circuit of the first candidate number as the circuit short - circuit of the second candidate number. For example, the circuit short - circuit of the first candidate number is the th circuit short - circuit, and the circuit short - circuit of the second candidate number is the th circuit short - circuit. At this time, the working parameter interval attenuation coefficient corresponding to the circuit short - circuit of the first candidate number is .

[0052] Secondly, determine the preset value (exemplarily illustrated by 1) and the working parameter interval attenuation coefficient of the circuit short - circuit of the first candidate number The difference ( ), based on the second product of the difference and the original upper limit of the operating parameters during normal operation of the circuit between the first candidate number of times and the second candidate number of times, determines the new original upper limit corresponding to the short circuit of the first candidate number of times of the circuit (the new original upper limit corresponding to the th short circuit of the circuit), that is ; The new original upper limit serves as the upper limit of the theoretical operating parameters corresponding to the transformer winding after the short circuit of the second candidate number of times (the th time).

[0053] Furthermore, determine the sum value of the preset value (exemplified by 1 for illustration) and the attenuation coefficient of the operating parameter range of the short circuit of the first candidate number of times of the circuit ( ), and based on the sum value and the third product of the original lower limit of the operating parameters during normal operation of the circuit between the first candidate number of times and the second candidate number of times, determine the new original lower limit corresponding to the short circuit of the first candidate number of times of the circuit (the new original lower limit corresponding to the th short circuit of the circuit), that is , The new original lower limit serves as the lower limit of the theoretical operating parameters corresponding to the transformer winding after the short circuit of the second candidate number of times (the th time).

[0054] Then, return to the step of selecting the short circuit of the first candidate number of times from several short circuits of the circuit until the theoretical operating parameter range corresponding to the transformer winding is determined after each short circuit, that is, determine the theoretical operating parameter range corresponding to the transformer winding after each short circuit , represents the new original lower limit corresponding to the th short circuit of the circuit for the th data dimension, represents the new original upper limit corresponding to the th short circuit of the circuit for the th data dimension.

[0055] It should be noted that for any data dimension, by determining whether the real-time obtained operating parameters are within the theoretical operating parameter range, it is determined whether there is a possibility of deformation of the transformer winding; among them, when the circuit where the transformer is located recovers from the short circuit, the operating parameters of the transformer will gradually recover, that is, from the abnormal parameters in the short circuit state to the normal parameters in normal operation. Therefore, the closer the time is to the moment of short circuit recovery, the higher the tolerance when comparing parameters.

[0056] In one implementation, in step S400, according to the theoretical operating parameter range and the operating parameters, determining the true deformation possibility of the transformer winding after each circuit short circuit includes steps S401 - S405: S401. Select the circuit short circuit of the first candidate number from several circuit short circuits, and determine the circuit short circuit of the previous time of the circuit short circuit of the first candidate number as the circuit short circuit of the second candidate number.

[0057] Optionally, select the circuit short circuit of the first candidate number from several circuit short circuits, and determine the circuit short circuit of the previous time of the circuit short circuit of the first candidate number as the circuit short circuit of the second candidate number. For example, the circuit short circuit of the first candidate number is the th circuit short circuit, and the circuit short circuit of the second candidate number is the th circuit short circuit.

[0058] S402. According to the operating parameters, determine the first target operating parameter when the circuit operates normally after the circuit short circuit of the first candidate number is restored, and the second target operating parameter when the circuit operates normally after the circuit short circuit of the second candidate number is restored, and respectively determine the first data change trend of the parameters of each data dimension during the circuit short circuit of the first candidate number and the parameters of each data dimension in the first target operating parameter, and respectively determine the second data change trend of the parameters of each data dimension during the circuit short circuit of the second candidate number and the parameters of each data dimension in the second target operating parameter.

[0059] Optionally, when the circuit short circuit of the first candidate number is restored, that is, after the th circuit short circuit is restored, at this time the circuit operates normally, and determine the first target operating parameter corresponding to the normal operation of the circuit at this time from the operating parameters. Similarly, when the circuit short circuit of the second candidate number is restored, that is, after the th circuit short circuit is restored, at this time the circuit operates normally, and determine the second target operating parameter corresponding to the normal operation of the circuit at this time from the operating parameters. Then, respectively determine the first data change trend of the parameters of each data dimension during the circuit short circuit of the first candidate number and the parameters of each data dimension in the first target operating parameter That is, the first data change trend corresponding to the parameter of the rd data dimension during the th circuit short circuit, and respectively determine the second data change trend of the parameters of each data dimension during the circuit short circuit of the second candidate number and the parameters of each data dimension in the second target operating parameter That is, the second data change trend corresponding to the parameter of the th - 1 data dimension during the The second data change trend corresponding to the parameters of each data dimension. It should be noted that when calculating the data change trend, it can be determined by calculating the difference. Taking the vibration frequency as an example, the average vibration frequency is calculated based on each vibration frequency in the first target working parameters, and then the difference between the average vibration frequency and the average vibration frequency when the circuit is short-circuited is determined, so as to determine the data change trend of the vibration frequency; the data change trend can also be determined by other methods. For example, the difference between any vibration frequency in the first target working parameters and any vibration frequency when the circuit is short-circuited is used to determine the data change trend of the vibration frequency, which is not specifically limited. The data change trends of other data dimensions are similar and will not be elaborated.

[0060] S403. Respectively, according to the first data change trend of the parameters of each data dimension and the second data change trend of the parameters of each data dimension of the difference and the normalization function , determine the parameter recovery difference corresponding to each data dimension each time the circuit is short-circuited.

[0061] Specifically, the calculation formula is: Among them, is the parameter recovery difference corresponding to the th data dimension at the th short circuit of the circuit.

[0062] S404. According to the working parameters and the theoretical working parameter range, determine the deformation possibility of the transformer winding reflected by each data dimension after each circuit short circuit.

[0063] First, compare the parameters of each data dimension in the working parameters after each circuit short circuit recovery with the corresponding theoretical working parameter range of the data dimension one by one. Exemplarily, taking the parameters of each data dimension in the working parameters at the real-time T moment after each circuit short circuit recovery as an example, represents the th circuit short circuit recovery. At the T moment, the parameter (actual parameter value) of the th data dimension is compared with the corresponding theoretical working parameter range of the data dimension one by one.

[0064] Secondly, when the parameter of any data dimension in the working parameters is greater than the upper limit of the theoretical working parameter of the corresponding data dimension's theoretical working parameter range, that is , determine the first absolute value of the difference between the parameter of this data dimension and the upper limit of the corresponding theoretical working parameter, according to the normalization function and the first absolute value , after determining the short circuit of the corresponding number of circuits, determine the deformation possibility of the transformer winding reflected by this data dimension , specifically referring to the th time after the circuit short circuit, at moment, the deformation possibility of the transformer winding reflected by the th data dimension.

[0065] Furthermore, when the parameter of any data dimension in the working parameters is less than the theoretical working parameter lower limit of the corresponding data dimension's theoretical working parameter range, that is , determine the second absolute value of the difference between the parameter of this data dimension and the corresponding theoretical working parameter lower limit , according to the normalization function and the second absolute value, determine the deformation possibility of the transformer winding reflected by this data dimension after the short circuit of the corresponding number of circuits : S405. According to the parameter recovery difference corresponding to each data dimension during each circuit short circuit and the deformation possibility of the transformer winding reflected by each data dimension after each circuit short circuit, determine the true deformation possibility of the transformer winding after each circuit short circuit.

[0066] First, determine the start time of each circuit short circuit, respectively determine the recovery time when the circuit returns to normal operation after the corresponding number of circuit short circuits, and respectively determine the elapsed time from the start time to the recovery time , that is, the elapsed time corresponding to the start of the th circuit short circuit to the recovery of the circuit short circuit.

[0067] Secondly, respectively according to the elapsed time and the parameter recovery difference , determine the data anomaly tolerance corresponding to each data dimension after each circuit short circuit , that is, the data anomaly tolerance corresponding to the th data dimension after the th circuit short circuit: Among them, the smaller the parameter recovery difference , the better the recovery effect, and the higher the data anomaly tolerance. The larger it is, when the elapsed time is smaller, it means the recovery time is shorter. At this time, the data is unstable and the tolerance for abnormal data is higher. The larger it is.

[0068] Furthermore, the reciprocal of the data anomaly tolerance corresponding to each data dimension after each circuit short - circuit is determined respectively , the preset weight (the preset weight of the th data dimension) and the deformation possibility of the transformer winding reflected by each data dimension after each circuit short - circuit of the fourth product .

[0069] Then, according to the fourth product and the number of dimensions of the data dimension, a sum average is performed, and according to the sum average result and the normalization function, the true deformation possibility of the transformer winding after each circuit short - circuit is determined. The specific calculation formula is: Wherein, represents the number of dimensions of the data dimension, is at time T after the th circuit short - circuit, and the true deformation possibility of the transformer winding. It should be noted that the possibility of transformer winding deformation is adjusted by the data anomaly tolerance. The higher the data anomaly tolerance, the lower the relative probability of transformer winding deformation.

[0070] In addition, for the deformation of the transformer winding, working parameters such as vibration frequency, vibration amplitude, and temperature correspond to its physical parameters, i.e., mechanical strength. Therefore, they have a stronger explanatory ability for deformation. For example, when the vibration intensity and temperature of the transformer winding are abnormal, the possibility of transformer winding deformation is higher. In summary, for vibration frequency, vibration amplitude, and temperature, preset weights can be set, and the preset weights of the remaining data dimensions .

[0071] In one implementation manner, in step S400, according to the true deformation possibility and the possibility threshold, the deformation monitoring result of the transformer winding is determined. Specifically: A possibility threshold is set in advance. When the true deformation possibility , it is determined that the transformer winding may be deformed, and further offline detection is performed. The methods of offline detection include but are not limited to low - voltage pulse method, short - circuit impedance method, and image analysis method, etc. Select a suitable offline detection method according to the actual situation. The offline detection method can determine the deformation characteristics of the transformer winding, so as to determine the deformation monitoring result indicating whether there is deformation. When the deformation monitoring result indicating the existence of deformation is obtained, the transformer winding can be physically repaired or replaced to ensure the normal operation of the transformer.

[0072] It should be noted that the possibility threshold Adjustable, for example, the initial value is set to , and this initial value is adjusted as the number of short - circuits increases. For example, the initial value is gradually decreased, and the magnitude of each decrease is , and the new initial value is - .

[0073] In the embodiment of the present application, by combining the working parameters of multiple short - circuits in the circuit where the transformer is located, and based on the time interval between adjacent short - circuits, the influence of the short - circuit on the transformer winding, the difference between the real - time obtained working parameters and the theoretical working parameter range, etc., a more accurate real deformation possibility of the transformer winding is obtained, making the accuracy of the final deformation monitoring result higher; at the same time, it is possible to determine the influence on the transformer winding by analyzing the parameter samples of multiple data dimensions and combining the design parameters of the transformer winding, improving the credibility of the deformation monitoring result, and the judgment method is relatively simple, and the delay in obtaining the result is low.

[0074] Referring to Figure 2 , a structural block diagram of a transformer winding deformation monitoring system according to an embodiment of the present application is shown. The system may include: An acquisition module, configured to acquire the design parameters of the transformer, and during the operation of the transformer, acquire the working parameters of the transformer. The operation process of the transformer includes normal circuit operation and several circuit short - circuits; A first determination module, configured to determine the influence intensity coefficient of the transformer winding during each circuit short - circuit according to the design parameters and the working parameters; A second determination module, configured to determine the theoretical working parameter range corresponding to the transformer winding after each circuit short - circuit according to the influence intensity coefficient and the working parameters; A monitoring module, configured to determine the real deformation possibility of the transformer winding after each circuit short - circuit according to the theoretical working parameter range and the working parameters, and determine the deformation monitoring result of the transformer winding according to the real deformation possibility and the possibility threshold.

[0075] In the embodiment of the present application, the functions of the various modules in the system can refer to the corresponding descriptions in the above - mentioned method, and will not be elaborated here.

[0076] Referring to Figure 3 , in an implementation manner, the embodiment of the present application further provides a transformer winding deformation monitoring device, including: a processor 310 and a memory 320. Instructions are stored in the memory 320, and these instructions are loaded and executed by the processor 310 to implement the above - mentioned transformer winding deformation monitoring method.

[0077] It should be noted that the above order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

Claims

1. A transformer winding deformation monitoring method, characterized in that: The method comprises: Acquire the design parameters of the transformer, and during the operation of the transformer, acquire the operating parameters of the transformer, wherein the operation of the transformer includes normal circuit operation and several circuit short circuits; Determine, based on the design parameters and the operating parameters, the affected intensity coefficient of the transformer winding each time the circuit is short-circuited; Determine, according to the affected intensity coefficient and the operating parameters, a theoretical operating parameter range corresponding to the transformer winding after each circuit short circuit; According to the theoretical operating parameter range and the operating parameters, the actual deformation possibility of the transformer winding after each circuit short circuit is determined, and according to the actual deformation possibility and the possibility threshold, the deformation monitoring result of the transformer winding is determined.

2. The transformer winding deformation monitoring method according to claim 1, characterized in that: The design parameters include the length of the winding conductor and the sum of the masses of the transformer winding and the iron core, and the operating parameters include parameters of several data dimensions, including the input current, output current, vibration amplitude, vibration frequency and temperature of the transformer winding; Determining the affected intensity coefficient of the transformer winding each time the circuit is short-circuited according to the design parameters and the operating parameters includes: Determining the short-circuit current value of the transformer each time the circuit is short-circuited according to the input-end current and the output-end current each time the circuit is short-circuited; Determining the electromotive force exerted on the transformer winding each time the circuit is short-circuited according to the short-circuit current value and the winding conductor length; Determine the electromotive force influence coefficient each time the circuit is short-circuited according to the vibration amplitude, vibration frequency, electromotive force applied to the transformer windings during the short-circuit, and the total mass each time the circuit is short-circuited; According to the temperature of the transformer winding, the average short-circuit temperature at each circuit short-circuit is determined, and according to the average short-circuit temperature, the electrodynamic influence coefficient and the duration of the circuit short-circuit, the influence intensity coefficient of the transformer winding at each circuit short-circuit is determined.

3. The transformer winding deformation monitoring method according to claim 2, characterized in that: The determining of the affected intensity coefficient of the transformer winding each time the circuit is short-circuited according to the short-circuit average temperature, the electrodynamic influence coefficient and the duration of the circuit short-circuit comprises: respectively determining the first product of the short-circuit average temperature, the electrodynamic influence coefficient and the time length; The affected intensity coefficient of the transformer winding each time a circuit short circuit occurs is determined according to the first product and the normalized function respectively.

4. The transformer winding deformation monitoring method according to any one of claims 1 to 3, characterized in that: The theoretical operating parameter range corresponding to the transformer winding after each circuit short circuit is determined according to the affected intensity coefficient and the operating parameter, including: Determine, according to the working parameters, a first time interval between two adjacent times of circuit short circuits and a second time interval between two adjacent times of circuit short circuits, and determine, according to the first time intervals, an attenuation weight of the transformer winding at each time of circuit short circuit; Determine the corresponding working parameter attenuation influence coefficients between two times of circuit short circuits according to the attenuation weight of the transformer winding each time the circuit is short-circuited, the affected intensity coefficient of the transformer winding each time the circuit is short-circuited, and the second time interval; Determine the working parameter interval attenuation coefficient of the transformer winding each time the circuit is short-circuited according to each of the working parameter attenuation influence coefficients and the normalized function; The original upper limits and original lower limits of the working parameters when the circuit is operating normally between two adjacent times of circuit short circuits are determined respectively, and the theoretical working parameter range corresponding to the transformer winding after each circuit short circuit is determined according to the original upper limits, the original lower limits and the working parameter interval attenuation coefficient; wherein the original upper limits of the working parameters include the original upper limits corresponding to the parameters of several data dimensions respectively, and the original lower limits of the working parameters include the original lower limits corresponding to the parameters of several data dimensions respectively.

5. The transformer winding deformation monitoring method according to claim 4, characterized in that: The determining of the theoretical operating parameter range corresponding to the transformer winding after each circuit short circuit according to the original upper limit, the original lower limit and the operating parameter interval attenuation coefficient includes: Selecting a first candidate number of circuit short circuits from a plurality of circuit short circuits, and determining a circuit short circuit preceding the first candidate number of circuit short circuits as a second candidate number of circuit short circuits; Determine a difference between a preset value and the attenuation coefficient of the working parameter interval of the circuit short circuit of the first candidate number of times, and determine a new original upper limit corresponding to the circuit short circuit of the first candidate number of times according to the difference and a second product of the original upper limit of the working parameter when the circuit is normally operated between the first candidate number of times and the second candidate number of times, as the theoretical upper limit of the working parameter corresponding to the transformer winding after the circuit short circuit of the second candidate number of times; Determine the sum of a preset value and the attenuation coefficient of the working parameter interval of the first candidate number of circuit short circuits, determine a new original lower limit corresponding to the first candidate number of circuit short circuits according to the sum and the third product of the original lower limit of the working parameter when the circuit is normally operated between the first candidate number and the second candidate number, as the theoretical working parameter lower limit corresponding to the transformer winding after the circuit is short circuited for the second candidate number of times, and determine the theoretical working parameter range corresponding to the transformer winding after the circuit is short circuited for the second candidate number of times according to the theoretical working parameter upper limit and the theoretical working parameter lower limit; Return to the step of selecting a first candidate number of circuit short circuits from a plurality of circuit short circuits, until a theoretical operating parameter range corresponding to the transformer winding after each circuit short circuit is determined.

6. The transformer winding deformation monitoring method according to claim 5, characterized in that: Determining the actual deformation possibility of the transformer winding after each circuit short circuit according to the theoretical operating parameter range and the operating parameters includes: Selecting a first candidate number of circuit short circuits from a number of circuit short circuits, and determining a circuit short circuit preceding the first candidate number of circuit short circuits as a second candidate number of circuit short circuits; Determine, according to the operating parameters, a first target operating parameter when the circuit operates normally after the circuit short circuit is restored for the first candidate number of times, and a second target operating parameter when the circuit operates normally after the circuit short circuit is restored for the second candidate number of times, and respectively determine a first data change trend of the parameters of each data dimension when the circuit is short-circuited for the first candidate number of times and the parameters of each data dimension in the first target operating parameter, and respectively determine a second data change trend of the parameters of each data dimension when the circuit is short-circuited for the second candidate number of times and the parameters of each data dimension in the second target operating parameter; Determine the parameter recovery difference corresponding to each data dimension each time the circuit is short-circuited according to the difference between the first data change trend of the parameter of each data dimension and the second data change trend of the parameter of each data dimension and the normalization function; Determine, according to the operating parameters and the theoretical operating parameter range, the deformation possibility of the transformer winding reflected by each data dimension after each circuit short circuit; According to the parameter recovery difference corresponding to each data dimension after each circuit short circuit and the deformation possibility of the transformer winding reflected by each data dimension during each circuit short circuit, the actual deformation possibility of the transformer winding after each circuit short circuit is determined.

7. The transformer winding deformation monitoring method according to claim 6, characterized in that: Determining the deformation possibility of the transformer winding reflected by each data dimension after each circuit short circuit according to the operating parameters and the theoretical operating parameter range includes: Compare the parameters of each data dimension in the working parameters after each circuit short circuit recovery with the theoretical working parameter range of the corresponding data dimension one by one; When the parameter of any data dimension of the working parameters is greater than the theoretical working parameter upper limit of the theoretical working parameter range of the corresponding data dimension, determine the first absolute value of the difference between the parameter of the data dimension and the corresponding upper limit of the theoretical working parameter, and determine the deformation possibility of the transformer winding reflected by the data dimension after the corresponding number of circuit short circuits according to the normalized function and the first absolute value; When the parameter of any data dimension among the working parameters is less than the theoretical working parameter lower limit of the theoretical working parameter range of the corresponding data dimension, determine the second absolute value of the difference between the parameter of the data dimension and the corresponding lower limit of the theoretical working parameter, and determine the deformation possibility of the transformer winding reflected by the data dimension after the corresponding number of circuit short circuits based on the normalized function and the second absolute value.

8. The transformer winding deformation monitoring method according to claim 6, characterized in that: The determining of the actual deformation possibility of the transformer winding after each circuit short circuit according to the parameter recovery difference corresponding to each data dimension after each circuit short circuit and the deformation possibility of the transformer winding reflected by each data dimension during each circuit short circuit includes: Determine the start time of each circuit short circuit, respectively determine the start time and the recovery time of the normal operation of the circuit after the corresponding number of circuit short circuits are restored, and respectively determine the elapsed time from the start time to the recovery time; Determine the data anomaly tolerance corresponding to each data dimension after each circuit short circuit according to the elapsed time and the parameter recovery difference; Respectively determine the reciprocal of the data anomaly tolerance corresponding to each data dimension after each circuit short circuit, the preset weight, and the fourth product of the deformation possibility of the transformer winding reflected by each data dimension after each circuit short circuit; A sum and an average are performed according to the fourth product and the number of dimensions of the data dimension, and a real deformation possibility of the transformer winding after each circuit short circuit is determined according to the sum and an average result and a normalized function.

9. A transformer winding deformation monitoring system, characterized in that: include: An acquisition module, used for acquiring design parameters of the transformer, and acquiring operating parameters of the transformer during the operation of the transformer, wherein the operation of the transformer includes normal circuit operation and several circuit short circuits; A first determination module is used to determine the affected intensity coefficient of the transformer winding each time the circuit is short-circuited according to the design parameters and the operating parameters; A second determination module is used to determine the theoretical operating parameter range corresponding to the transformer winding after each circuit short circuit according to the affected intensity coefficient and the operating parameter; The monitoring module is used to determine the actual deformation possibility of the transformer winding after each circuit short circuit based on the theoretical working parameter range and the working parameters, and to determine the deformation monitoring result of the transformer winding based on the actual deformation possibility and the possibility threshold.

10. A transformer winding deformation monitoring device, characterized in that: include: A processor and a memory, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the method according to any one of claims 1 to 8.

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