Transformer partial discharge positioning method and system based on energy accumulation method and Chan algorithm

Abstract

The invention discloses a transformer partial discharge positioning method and system based on an energy accumulation method and a Chan algorithm. The method comprises the steps that threshold energy of a partial discharge signal sequence is obtained through calculation; sampling points are inserted into the front end and the rear end of the sensor, and an energy inflection point of the partial discharge signal after the sampling points are inserted is solved by using an improved energy accumulation method; calculating the signal arrival time difference of the reference sensor and the non-reference sensor; and based on an improved Chan algorithm, constructing a general solution containing a positioning error variable and a target optimization function, obtaining an optimal solution of the positioning error variable by solving the target optimization function, obtaining a linear propagation distance from the partial discharge signal to the reference sensor based on the optimal solution, and substituting the linear propagation distance into the general solution to obtain a positioning result. According to the method, time difference calculation errors are solved, and the defect that a closed solution of a traditional Chan algorithm is sensitive to measurement errors is overcome. The positioning precision is greatly improved in a complex scene in the transformer, and the actual requirement of engineering for the positioning accuracy is met.

Description

Technical Field

[0001] This invention relates to the field of power equipment condition monitoring and fault location technology, and in particular to a transformer partial discharge location method based on the energy accumulation method and the Chan algorithm. Background Technology

[0002] Partial discharge (PD) is a key indicator of insulation degradation in power transformers, and its accurate location is crucial for equipment condition assessment and fault early warning. With the development of smart grids and online monitoring technologies, partial discharge location methods based on multiple physical quantities such as sound, electricity, and light have become a research hotspot.

[0003] Among various positioning technologies, UHF technology is gradually being applied to the spatial positioning of local discharge power supplies inside electrical equipment due to its strong resistance to electromagnetic interference. The positioning algorithm based on time difference of arrival (TDOA) is the core of UHF positioning. The traditional Chan algorithm is widely used in this field because it does not require iteration and has the characteristics of closed-form solution.

[0004] Existing UHF positioning mainly relies on the traditional Chan algorithm. It detects partial discharge signals using UHF sensors, calculates the time difference of arrival (TDOA) of the signals to different sensors, and then substitutes the time difference into the closed-form solution of the traditional Chan algorithm to obtain the spatial location of the partial discharge source, thus realizing the partial discharge positioning of the transformer.

[0005] However, the research found that the transformer has a complex internal structure, and the propagation path of the UHF signal is blocked by components such as windings and iron core, resulting in non-line-of-sight propagation and attenuation distortion, which leads to errors in time difference calculation. The traditional Chan algorithm is extremely sensitive to the time difference calculation results and has low robustness, ultimately resulting in excessive positioning errors that cannot meet the actual engineering needs. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a transformer partial discharge location method based on the energy accumulation method and the Chan algorithm, which can effectively improve the accuracy of partial discharge location.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a transformer partial discharge localization method based on the energy accumulation method and the Chan algorithm, comprising: The partial discharge signal sequence is obtained by using sensors deployed on the transformer, and a reference sensor and amplitude threshold are preset to calculate the threshold energy of the partial discharge signal sequence. Based on the threshold energy, sampling points are inserted at both the front and back ends of the sensor. An improved energy accumulation method is used to solve for the energy inflection point of the partial discharge signal after the sampling points are inserted. The time difference of signal arrival between the reference sensor and the non-reference sensor is calculated based on the energy inflection point and the number of inserted sampling points. Based on the sensor position, the time difference of arrival of signals from the reference sensor and the non-reference sensor, and using the improved Chan algorithm, a general solution containing positioning error variables and a target optimization function are constructed. The optimal solution for the positioning error variables is obtained by solving the target optimization function. Based on the optimal solution, the straight-line propagation distance of the partial discharge signal to the reference sensor is obtained, and the result is obtained by substituting it into the general solution.

[0008] As a further technical solution, the threshold energy of the partial discharge signal sequence is calculated as follows: based on the maximum amplitude of the background noise received by the sensor, a preset amplitude threshold is established, and the threshold energy of the partial discharge signal sequence is expressed as: ;in, The threshold energy of the partial discharge signal sequence. This represents the number of sampling points in the partial discharge signal sequence. The amplitude of the partial discharge signal sequence is limited by the amplitude threshold.

[0009] As a further technical solution, the amplitude of the inserted sampling points is 0, and the method for determining the number of inserted sampling points is as follows: First, calculate the average energy of the partial discharge signal sequence, and then calculate the number of inserted sampling points at the front and rear ends of the sensor as follows: ;in, The number of each inserted sampling point, This is the rounding function. The average energy of the partial discharge signal sequence. The threshold energy of the partial discharge signal sequence. Number of sampling points in the partial discharge signal sequence.

[0010] As a further technical solution, the method for solving the energy inflection point of the partial discharge signal after the insertion sampling point is as follows: First, obtain the improved energy accumulation function of the partial discharge signal after the insertion sampling point: ;in, To improve the energy accumulation function, The partial discharge signal after the insertion of sampling points is the first Improved cumulative energy value for each sampling point , The sampling point number, The partial discharge signal after the insertion of sampling points is the first The signal amplitude at each sampling point. The threshold energy of the partial discharge signal sequence. The number of sampling points in the partial discharge signal sequence; Then, based on the improved energy accumulation function, the method for obtaining the energy inflection point of the partial discharge signal is as follows: ;in, To find the variable value corresponding to the minimum value of the function.

[0011] As a further technical solution, the method for calculating the signal arrival time difference between the reference sensor and the non-reference sensor is as follows: ;in, The time difference between the arrival of signals from the reference sensor and the non-reference sensor. For signal sampling rate, This represents the energy inflection point of the partial discharge signal after the non-reference sensor is inserted into the sampling point. This refers to the number of sampling points inserted at both the front and rear ends of the non-reference sensor. The energy inflection point of the partial discharge signal after the reference sensor is inserted at the sampling point. The number of sampling points inserted at the front and back ends of the reference sensor.

[0012] As a further technical solution, the method for constructing a general solution including positioning errors is as follows: First, the matrix equation is obtained based on the Chan algorithm, which is expressed as: ; In the formula, ; ; ;in, Let the coordinate vector of the power source position be denoted as . The distance the partial discharge signal travels in a straight line from the reference sensor. , , For matrix coefficients, This refers to the propagation speed of the partial discharge signal. Based on the matrix equation and the positioning error, the general solution is expressed as: ;in, , , For the positioning error variable, , , , , , These are the equation coefficients.

[0013] As a further technical solution, the objective optimization function is constructed as follows: ; ; ; ; ; ; in, , , These are the length, width, and height of the transformer housing, respectively. For about R The discriminant of a quadratic equation in one variable.

[0014] Secondly, the present invention provides a transformer partial discharge location system based on the energy accumulation method and the Chan algorithm, comprising the following modules: The threshold energy calculation module is configured to: obtain the partial discharge signal sequence based on the sensor deployed on the transformer, and calculate the threshold energy of the partial discharge signal sequence by preset reference sensor and amplitude threshold. The energy inflection point calculation module is configured to: insert sampling points at both the front and rear ends of the sensor based on a threshold energy, and use an improved energy accumulation method to solve for the energy inflection point of the partial discharge signal after the sampling points are inserted; The time difference of arrival (TDOA) calculation module is configured to calculate the time difference of arrival between the reference sensor and the non-reference sensor based on the energy inflection point and the number of inserted sampling points. The positioning module is configured to: construct a general solution including positioning error and a target optimization function based on the sensor position, the time difference of arrival of the signals from the reference sensor and the non-reference sensor, and based on the improved Chan algorithm; obtain the optimal solution of positioning error by solving the target optimization function; obtain the straight-line propagation distance of the partial discharge signal to the reference sensor based on the optimal solution; and substitute it into the general solution to obtain the positioning result.

[0015] One or more technical solutions of the present invention have the following beneficial effects: This invention first employs an improved energy accumulation method, which, through the steps of "presetting an amplitude threshold based on background noise and calculating the threshold energy → inserting zero-amplitude sampling points at both ends of the partial discharge signal to optimize the signal energy distribution → locating the signal energy inflection point," effectively counteracts the effects of signal diffraction and reflection distortion caused by the windings and core of the transformer, accurately captures key signal feature points, significantly reduces the time difference calculation error caused by non-line-of-sight propagation, and provides a high-precision time difference data foundation for subsequent positioning.

[0016] The improved Chan algorithm of this invention introduces a positioning error variable, establishes a correlation between the local discharge source coordinates and the error variable, constructs an objective optimization function containing the positioning error variable, and performs global optimization in conjunction with an optimization algorithm, thus solving the defect of the traditional Chan algorithm's closed-form solution being sensitive to measurement errors. Even if there are small residual errors in the time difference, their impact on the positioning results can be offset by the dynamic optimization of the error variable, significantly improving positioning accuracy in complex scenarios inside transformers and meeting the practical engineering requirements for positioning accuracy. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0018] Figure 1 This is a flowchart of the transformer partial discharge localization method based on the energy accumulation method and the Chan algorithm in this invention; Figure 2 This is a waveform diagram of the partial discharge signal received by the reference sensor in this invention; Figure 3 The diagram shows the waveform of the reference sensor signal after inserting a certain number of sampling points in this invention, as well as the improved energy accumulation function curve. Detailed Implementation

[0019] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] Example 1 This embodiment uses the example of installing six ultra-high frequency sensors inside a full-size transformer with dimensions of 4.75×2.3×2.67 m to illustrate the implementation of the method of the present invention.

[0021] This embodiment provides a transformer partial discharge localization method based on the energy accumulation method and the Chan algorithm, such as... Figure 1 As shown, the specific steps are as follows: S1: Based on the partial discharge signal sequence obtained by the sensor deployed on the transformer, and with the preset reference sensor and amplitude threshold, the threshold energy of the partial discharge signal sequence is calculated.

[0022] In step S1, a spatial rectangular coordinate system is established with one bottom corner of the transformer tank to record the position coordinates of the deployed UHF sensor, based on the maximum amplitude of the background noise received by the sensor. Preset amplitude threshold .

[0023] The threshold energy of a partial discharge signal sequence is expressed as: ;in, The threshold energy of the partial discharge signal sequence. This represents the number of sampling points in the partial discharge signal sequence. Amplitude threshold Amplitude of partial discharge signal sequence under constraints.

[0024] Partial discharge signal sequence amplitude The calculation formula is: ;in, The first partial discharge signal The signal amplitude at each sampling point.

[0025] In this embodiment, the sensor (Reference sensor) Coordinates (0.818, 0, 2.038) m; Sensor Coordinates (4.090, 0.310, 1.096) m; Sensor Coordinates (4.750, 2.105, 1.416) m; Sensor Coordinates (2.900, 1.990, 1.096) m; Sensor Coordinates (0.663, 1.990, 1.646) m; Sensor Coordinates (0, 1.505, 1.096) m.

[0026] The boost voltage enables each UHF sensor to detect partial discharge UHF signals, with the reference sensor being a prime example. For example, The maximum amplitude of the signal background noise is approximately = 0.07V, the maximum amplitude of the partial discharge signal exceeds 1.4V, therefore the amplitude threshold is set to 0.07V. T = 3 = 0.21V, such as Figure 2 As shown.

[0027] Reference sensor Number of sampling points for partial discharge signal N =14000, substituting into the above... In the formula, the reference sensor is calculated. Threshold energy of partial discharge signal sequence It is 0.0022497 V. 2 .

[0028] S2: Based on the threshold energy, sampling points with an amplitude of 0 are inserted at both the front and back ends of the sensor.

[0029] In step S2, the method for determining the number of inserted sampling points is as follows: First, calculate the average energy of the partial discharge signal sequence. : ;in, The first partial discharge signal Signal amplitude at each sampling point This represents the number of sampling points in the partial discharge signal sequence.

[0030] When the amplitude of a partial discharge signal is large, it will cause the average energy of the original signal sequence to increase. The average energy of the signal sequence is relatively high. and N Inversely proportional, by appropriately increasing N The quantity can be reduced .

[0031] Therefore, it is possible to insert [something] at both the front and rear ends of the sensor. The number of sampling points is [number], and the amplitude of the inserted sampling point is 0, thereby reducing [the amplitude]. The purpose is to calculate the number of sampling points inserted at both the front and rear ends of the sensor. ;in, The number of each inserted sampling point, This is the rounding function. The average energy of the partial discharge signal sequence. The threshold energy of the partial discharge signal sequence. The number of sampling points in the partial discharge signal sequence. Based on the above method, the number of insertion sampling points for each UHF sensor signal can be calculated. .

[0032] In this embodiment, a reference sensor is used. For example, the reference sensor is calculated according to the above formula. The average energy of the partial discharge signal sequence 0.0070746V 2 The reference sensor can be derived based on the threshold energy. The number of inserted sampling points is: ; Therefore, in the reference sensor 15013 sampling points are inserted at both the front and back ends. The amplitude of the newly inserted sampling points is 0. The reference sensor after insertion... The total number of signal sampling points is 44,026.

[0033] S3: Using the improved energy accumulation method, the energy inflection point of the partial discharge signal after the sampling point is inserted is solved.

[0034] In step S3, the method for determining the energy inflection point of the partial discharge signal after the sampling point is as follows: First, the improved energy accumulation function of the partial discharge signal after the insertion of sampling points is obtained: ;in, To improve the energy accumulation function, The partial discharge signal after the insertion of sampling points is the first Improved cumulative energy value for each sampling point , These are the sampling point numbers, all of which are positive integers. j ∈[1, N+ 2 ]; The partial discharge signal after the insertion of sampling points is the first The signal amplitude at each sampling point. The threshold energy of the partial discharge signal sequence. The number of sampling points in the partial discharge signal sequence; Then, based on the improved energy accumulation function, the method for obtaining the energy inflection point of the partial discharge signal is as follows: ;in, To find the variable value corresponding to the minimum value of the function, Represents the improved energy accumulation function The sampling point number corresponding to the minimum value is the energy inflection point of the partial discharge signal after the sampling point is inserted. Based on the above method, the energy inflection point of each UHF sensor signal can be calculated. .

[0035] In this embodiment, a reference sensor is used. For example, using the improved energy accumulation method, the solution for the reference sensor with 2×15013 additional sampling points is obtained. energy inflection point of the signal .

[0036] First, using the corresponding formulas mentioned above, the reference sensor after inserting a certain number of sampling points is obtained. Improved energy accumulation function:

[0037] The reference sensor after inserting 2×15013 sampling points The signal waveform and the improved energy accumulation function curve are shown below. Figure 3 As shown.

[0038] Based on the improved energy accumulation function, the energy inflection point of the signal after inserting a certain number of sampling points can be found. P Calculations show that the reference sensor with 2×15013 sampling points is... signal The value is 21984.

[0039] S4: Calculate the signal arrival time difference between the reference sensor and the non-reference sensor based on the energy inflection point and the number of inserted sampling points.

[0040] In step S4, a reference sensor is assumed. Non-reference sensor The original signal length is L The method for calculating the time difference between the signals arriving at the reference sensor and the non-reference sensor is as follows: ;in, The time difference between the signals arriving at the reference sensor and the non-reference sensor, measured in nanoseconds (ns). The signal sampling rate (unit: GS / s) This represents the energy inflection point of the partial discharge signal after the non-reference sensor is inserted into the sampling point. This refers to the number of sampling points inserted at both the front and rear ends of the non-reference sensor. The energy inflection point of the partial discharge signal after the reference sensor is inserted at the sampling point. The number of sampling points inserted at the front and back ends of the reference sensor.

[0041] In this embodiment, calculations are performed using a non-reference sensor. With reference sensor Taking the signal arrival time difference as an example. Assuming a reference sensor... Non-reference sensor The original signal length is L = 14000, reference sensor 15013 sampling points were inserted at both the front and back ends of the sensor, resulting in an energy inflection point number of 21984 for the signal. (Non-reference sensor) 16537 sampling points were inserted at both the signal front-end and back-end. After insertion, the energy inflection point number of the signal was 23548. The signal sampling rate was uniformly set to 5 GS / s. Then, the reference sensor... Non-reference sensor signal delay Size: ; Therefore, the reference sensor Non-reference sensor The signal delay is 8 ns.

[0042] S5: Based on the sensor position, the time difference between the signals from the reference sensor and the non-reference sensor, and based on the improved Chan algorithm, construct a general solution including the positioning error and a target optimization function. Solve the target optimization function to obtain the optimal solution for the positioning error. Based on the optimal solution, obtain the straight-line propagation distance of the partial discharge signal to the reference sensor, and substitute it into the general solution to obtain the positioning result.

[0043] In step S5, the method for constructing the general solution including the positioning error is as follows: First, the matrix equation is obtained based on the Chan algorithm, expressed as: ; In the formula, ; ; ;in, Let the coordinate vector of the power source position be denoted as . The distance the partial discharge signal travels in a straight line from the reference sensor. , , For matrix coefficients, This refers to the propagation speed of the partial discharge signal. Transform the above matrix equation into two linear equations and solve them, that is, for and Solve this problem. The solution is denoted as = [ u 1 u 2 u 3] T , Will The solution is denoted as = [ v 1 v 2 v 3] T Assuming there is a positioning error = [ w 1 w 2 w 3] T Therefore, the coordinates of the local discharge source can be expressed as: ; Based on the matrix equation and the positioning error, the general solution is expressed as: ;in, , , For the positioning error variable, , , , , , These are the equation coefficients.

[0044] Based on the above process, it can be concluded that... x, y, z The result is only related to the variable R , w 1 、w 2 、w Regarding point 3, in order to reduce variables, it is necessary to... R Also adopted w 1 、w 2 、w 3 indicates that, according to the formula for the straight-line distance between the discharge source and the reference sensor: ; Substituting the general solution of the partial discharge source coordinates into the formula for the distance between the discharge source and the reference sensor, we can obtain the following about... R A quadratic equation in one variable can be solved using the quadratic formula. R The solution is: ; in, for R The discriminant of a quadratic equation in one variable is expressed as: ; To solve for the positioning error X 3 = [ w 1 w 2 w 3] T Construct the objective optimization function: ; ; ; ; ; ; in, , , These are the length, width, and height of the transformer housing, respectively. For about R The discriminant of a quadratic equation in one variable.

[0045] Transforming the constraints into a penalty function yields an augmented objective function, from which the optimal solution can be obtained through iterative optimization using an intelligent optimization algorithm. w 1 、w 2 、w 3.w 1 、w 2 、w 3 Substitute R The calculation formula is used to obtain R The value, and finally w 1 、w 2 、w 3 and R Substituting the general solution expression for the partial discharge source coordinates, the coordinates of the partial discharge source are obtained. x , y , z ).

[0046] In this embodiment, the propagation speed of the ultra-high frequency signal is set to a constant value. c = 0.2 m / ns, reference sensor Non-reference sensor ~ The signal arrival time differences were -10.8 ns, -4 ns, -1.2 ns, 6.4 ns, and 5.2 ns, respectively.

[0047] Let the coordinate vector of the discharge source position to be solved be... X = [ xyz ] T UHF signal from partial discharge source to reference sensor The straight-line propagation distance is R Substituting the sensor coordinates and signal arrival time difference into the matrix equation obtained based on the Chan algorithm, the result is as follows: ; After converting it into two linear equations, the solution is: ; ; Will The solution is denoted as = [ u 1 u 2 u 3] T , Will The solution is denoted as =[ v 1 v 2 v 3] T Assuming there is a positioning error = [ w 1 w 2 w 3] T ,in u 1 = 2.310, u 2 = 1.681, u3 = 3.288 v 1 = 0.533 v 2 = -0.768, v 3 = -0.649.

[0048] The general solution is expressed as: ; Formula for the straight-line distance between the power supply and the reference sensor: ; R The solution is: ; in, Let be the discriminant of a quadratic equation in one variable, expressed as: ; The objective optimization function is constructed as follows:

[0049] The optimal solution can be obtained through iterative analysis using the particle swarm optimization algorithm. w 1 = -0.1856, w 2 = 0.4690, w 3 = 0.4784, therefore Δ = 1.5662, from which we can obtain R = 2.7983, the coordinates of the local discharge source are (3.615, 0, 1.95) m, and the positioning error is 0.114 m.

[0050] Example 2 This embodiment provides a transformer partial discharge location system based on the energy accumulation method and the Chan algorithm, including the following modules: The threshold energy calculation module is configured to: obtain the partial discharge signal sequence based on the sensor deployed on the transformer, and calculate the threshold energy of the partial discharge signal sequence by preset reference sensor and amplitude threshold. The energy inflection point calculation module is configured to: insert sampling points at both the front and rear ends of the sensor based on a threshold energy, and use an improved energy accumulation method to solve for the energy inflection point of the partial discharge signal after the sampling points are inserted; The time difference of arrival (TDOA) calculation module is configured to calculate the time difference of arrival between the reference sensor and the non-reference sensor based on the energy inflection point and the number of inserted sampling points. The positioning module is configured to: construct a general solution including positioning error and a target optimization function based on the sensor position, the time difference of arrival of the signals from the reference sensor and the non-reference sensor, and based on the improved Chan algorithm; obtain the optimal solution of positioning error by solving the target optimization function; obtain the straight-line propagation distance of the partial discharge signal to the reference sensor based on the optimal solution; and substitute it into the general solution to obtain the positioning result.

[0051] Various modifications and variations of this invention will be apparent to those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A transformer partial discharge localization method based on energy accumulation method and Chan algorithm, characterized in that, include: The partial discharge signal sequence is obtained by using sensors deployed on the transformer, and the threshold energy of the partial discharge signal sequence is calculated by presetting a reference sensor and an amplitude threshold. Based on the threshold energy, sampling points are inserted at both the front and back ends of the sensor. An improved energy accumulation method is used to solve for the energy inflection point of the partial discharge signal after the sampling points are inserted. The time difference of signal arrival between the reference sensor and the non-reference sensor is calculated based on the energy inflection point and the number of inserted sampling points. Based on the sensor position, the time difference of arrival of signals from the reference sensor and the non-reference sensor, and using the improved Chan algorithm, a general solution containing positioning error variables and a target optimization function are constructed. The optimal solution for the positioning error variables is obtained by solving the target optimization function. Based on the optimal solution, the straight-line propagation distance of the partial discharge signal to the reference sensor is obtained, and the result is obtained by substituting it into the general solution.

2. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The threshold energy of the partial discharge signal sequence is calculated as follows: based on the maximum amplitude of the background noise received by the sensor, a preset amplitude threshold is established, and the threshold energy of the partial discharge signal sequence is expressed as: ;in, The threshold energy of the partial discharge signal sequence. This represents the number of sampling points in the partial discharge signal sequence. The amplitude of the partial discharge signal sequence is limited by the amplitude threshold.

3. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The amplitude of the inserted sampling points is 0, and the method for determining the number of inserted sampling points is as follows: First, calculate the average energy of the partial discharge signal sequence, and then calculate the number of inserted sampling points at the front and rear ends of the sensor as follows: ;in, The number of each inserted sampling point, This is the rounding function. The average energy of the partial discharge signal sequence. The threshold energy of the partial discharge signal sequence. Number of sampling points in the partial discharge signal sequence.

4. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The method for solving the energy inflection point of the partial discharge signal after the insertion sampling point is as follows: First, obtain the improved energy accumulation function of the partial discharge signal after the insertion sampling point: ;in, To improve the energy accumulation function, The partial discharge signal after the insertion of sampling points is the first Improved cumulative energy value for each sampling point , The sampling point number, The partial discharge signal after the insertion of sampling points is the first The signal amplitude at each sampling point. The threshold energy of the partial discharge signal sequence. The number of sampling points in the partial discharge signal sequence; Then, based on the improved energy accumulation function, the method for obtaining the energy inflection point of the partial discharge signal is as follows: ;in, To find the variable value corresponding to the minimum value of the function.

5. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The method for calculating the time difference of signal arrival between the reference sensor and the non-reference sensor is as follows: ;in, The time difference between the arrival of signals from the reference sensor and the non-reference sensor. For signal sampling rate, This represents the energy inflection point of the partial discharge signal after the non-reference sensor is inserted into the sampling point. This refers to the number of sampling points inserted at both the front and rear ends of the non-reference sensor. The energy inflection point of the partial discharge signal after the reference sensor is inserted at the sampling point. The number of sampling points inserted at the front and back ends of the reference sensor.

6. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The method for constructing the general solution including positioning error is as follows: First, the matrix equation is obtained based on the Chan algorithm, which is expressed as: ； In the formula, ; ; ;in, Let be the coordinate vector of the power source location. The distance the partial discharge signal travels in a straight line from the reference sensor. , , For matrix coefficients, This refers to the propagation speed of the partial discharge signal. Based on the matrix equation and the positioning error, the general solution is expressed as: ;in, , , For the positioning error variable, , , , , , These are the equation coefficients.

7. The transformer partial discharge location method based on energy accumulation method and Chan algorithm as described in claim 1, characterized in that, The objective optimization function is constructed as follows: ; ; ; ; ; ; in, , , These are the length, width, and height of the transformer housing, respectively. For about R The discriminant of a quadratic equation in one variable.

8. A transformer partial discharge location system based on the energy accumulation method and Chan algorithm, characterized in that, Includes the following modules: The threshold energy calculation module is configured to: obtain the partial discharge signal sequence based on the sensor deployed on the transformer, and calculate the threshold energy of the partial discharge signal sequence by preset reference sensor and amplitude threshold. The energy inflection point calculation module is configured to: insert sampling points at both the front and rear ends of the sensor based on a threshold energy, and use an improved energy accumulation method to solve for the energy inflection point of the partial discharge signal after the sampling points are inserted; The time difference of arrival (TDOA) calculation module is configured to calculate the time difference of arrival between the reference sensor and the non-reference sensor based on the energy inflection point and the number of inserted sampling points. The positioning module is configured to: construct a general solution including positioning error and a target optimization function based on the sensor position, the time difference of arrival of the signals from the reference sensor and the non-reference sensor, and based on the improved Chan algorithm; obtain the optimal solution of positioning error by solving the target optimization function; obtain the straight-line propagation distance of the partial discharge signal to the reference sensor based on the optimal solution; and substitute it into the general solution to obtain the positioning result.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the transformer partial discharge location method based on the energy accumulation method and the Chan algorithm as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the transformer partial discharge location method based on the energy accumulation method and the Chan algorithm as described in any one of claims 1-7.

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