Impedance matrix data generation method and impedance detection system of transformer

Abstract

The invention relates to the technical field of transformer detection, in particular to an impedance matrix data generation method and an impedance detection system.The impedance detection system executes the method to generate impedance matrix data, and the method comprises the steps that whether the transformer is online or not is judged through a voltage transformer and a current transformer; if the on-line voltage signal and the on-line current signal of each port are directly collected on line, calculating the on-line impedance vector and all on-line mutual impedances of the port according to the specific frequency point of the operation of the transformer, and splicing an on-line impedance matrix; otherwise, broadband off-line detection is carried out, and an off-line impedance matrix is spliced; secondly, eliminating external influences of the two impedance matrixes, and marking effective impedance matrix data and invalid impedance matrix data; the problem of monitoring and fault diagnosis omission caused by impedance matrix data frequency point limitation and the problem of monitoring and fault diagnosis result error caused by external influence are solved.

Description

Technical Field

[0001] This invention relates to the field of transformer testing technology, and in particular to a method for generating impedance matrix data of a transformer and an impedance testing system. Background Technology

[0002] Transformers are critical equipment in power systems, and their operating status directly affects the reliability and security of the power grid. Currently, transformer condition monitoring and fault diagnosis mainly rely on port impedance measurement methods, such as detecting the current and voltage at each port, calculating the impedance of each port, and then arranging the impedances of each port according to the port number to form an impedance matrix. The impedance matrix is ​​then used to further analyze and evaluate the condition of the transformer (such as whether the internal core, windings, etc. are damaged or deformed).

[0003] However, this impedance matrix data only shows the voltage and current at specific frequency points during transformer operation (such as the fundamental frequency 50Hz / 60Hz and specific harmonics with significant energy: 2nd harmonic 100Hz, 3rd harmonic 150Hz, 5th harmonic 250Hz, etc.), which cannot fully reflect the condition of the transformer, leading to omissions in monitoring and fault diagnosis.

[0004] In addition, this impedance matrix data does not eliminate the systematic influence of the current transformer status (such as external influences such as changes in oil temperature and load current) on the impedance measurement value. Changes in impedance characteristics caused by non-transformer internal faults will affect the subsequent algorithm's judgment of the transformer status, leading to errors in monitoring and fault diagnosis results. Summary of the Invention

[0005] To address the aforementioned shortcomings, the present invention aims to propose a method for generating impedance matrix data of a transformer and an impedance detection system, which solves the problems of missed monitoring and fault diagnosis caused by the frequency limitations of impedance matrix data and the problems of erroneous monitoring and fault diagnosis results caused by external influences.

[0006] To achieve this objective, the present invention adopts the following technical solution: A method for generating impedance matrix data of a transformer includes the following steps: A1: When the output signals of voltage transformers and current transformers on multiple ports of the transformer are detected, the online voltage signal and online current signal of each port of the transformer are synchronously collected through the voltage transformers and current transformers respectively, and then step A2 is executed; otherwise, step A3 is executed. A2: Based on the specific frequency of transformer operation, calculate the online impedance vector of each port and the online mutual impedance between the port and other ports by collecting the online voltage and online current signals from each port. Then, concatenate all online mutual impedances at the same frequency into an online impedance matrix and proceed to step A4. A3: Actively inject multiple frequency signals into multiple ports of the transformer using a wideband frequency response detection device, wait for the response, and obtain offline voltage and offline current signals; calculate the offline impedance vector of each port and the offline mutual impedance between the port and other ports from the offline voltage and offline current signals of each port, and splice all offline mutual impedances at the same frequency point into an offline impedance matrix, and then execute step A4. A4: Based on at least one externally influencing physical quantity, normalize the online impedance matrix and the offline impedance matrix respectively, and calculate the condition number for each online impedance matrix and each offline impedance matrix, and then proceed to step A5; A5: When the condition number of an online impedance matrix or offline impedance matrix exceeds a preset threshold, the corresponding online impedance matrix or offline impedance matrix is ​​invalidated, and all other online impedance matrices and offline impedance matrices are valid data.

[0007] Furthermore, step A4 includes the following sub-steps: A41: Based on the top oil temperature of the transformer, the online impedance matrix and the offline impedance matrix are normalized for the first time. A42: Based on the load current of the transformer, the online impedance matrix and the offline impedance matrix are normalized a second time. A43: Calculate the condition numbers for the online impedance matrix and the offline impedance matrix after the second normalization process.

[0008] Furthermore, sub-step A41 includes: The formula for the first normalization process is: ; k R =(C ref +235)\( C oil +235); k X =1; in: This refers to the online or offline impedance matrix after the first normalization process. The online or offline impedance matrix before the first normalization process, k R k is the resistance normalization factor. X C is the reactance normalization factor. ref As the reference temperature value, C oil This refers to the top oil temperature value. The online impedance matrix and the offline impedance matrix are normalized for the first time using the first normalization formula.

[0009] Furthermore, sub-step A42 includes: The formula for the second normalization process is: ; in: The resistance after the second normalization process. The resistance after the first normalization process. This is the rated load current. For load current, Custom calculation factors; The resistance of each online impedance vector in the online impedance matrix is ​​normalized a second time using the second normalization formula, and the resistance of each offline impedance vector in the offline impedance matrix is ​​normalized a second time using the second normalization formula.

[0010] Furthermore, in step A2, the online voltage signal and online current signal acquired at each port are used to calculate the online impedance vector of that port through a synchronous lock-in amplifier.

[0011] Furthermore, in step A3, the broadband frequency response detection equipment uses a frequency response analyzer.

[0012] Furthermore, in step A3, the offline voltage signal and offline current signal of each port are first denoised using the wavelet thresholding method, and then the offline impedance vector of that port is calculated.

[0013] Furthermore, in step A3, the offline voltage signal and offline current signal of each port are used to calculate the offline impedance vector of that port through Fourier transform.

[0014] An impedance detection system includes a broadband frequency response detection device, a data host, multiple voltage transformers, multiple current transformers, and at least one detection sensor; the voltage transformers and current transformers are electrically connected to the ports of the transformers, the ports of the transformers are all electrically connected to the broadband frequency response detection device, and the detection sensor, the broadband frequency response detection device, the voltage transformers, and the current transformers are all electrically connected to the data host. The detection sensor is used to detect physical quantities that are affected by external factors. The data host executes a program according to the above-described method for generating impedance matrix data of a transformer to generate impedance matrix data.

[0015] The technical solution provided by this invention can include the following beneficial effects: First, execute step A1 to see if the data host can obtain signals from the voltage transformers and current transformers on multiple ports of the transformer. If so, it proves that the transformer is currently running and is in an online state; otherwise, the transformer is in an offline state. If it is in an online state (step A2), calculate the online impedance matrix obtained at specific frequency points (such as the fundamental frequency 50Hz / 60Hz and specific harmonics with significant energy: 2nd harmonic 100Hz, 3rd harmonic 150Hz, 5th harmonic 250Hz, etc.) when the transformer is running. If it is in an offline state (step A3), actively inject multiple frequency signals into multiple ports of the transformer through a broadband frequency response detection device to calculate the offline impedance matrix at more frequency points. The combination of online impedance matrix data and offline impedance matrix data reflects the condition of the transformer more comprehensively, avoiding omissions in monitoring and fault diagnosis.

[0016] Meanwhile, regardless of whether online or offline detection is performed, the resulting matrix data is affected by the current transformer condition. For example, changes in oil temperature can cause slight thermal expansion and contraction of windings and structural components, leading to minor changes in leakage inductance. If this is not eliminated, it will affect the accuracy of the matrix data. Therefore, based on the physical quantities affected by external factors on the transformer (selected according to the actual situation), the matrix is ​​normalized (i.e., step A4) to optimize the data. This allows the focus to be placed on changes in intrinsic impedance characteristics caused by internal transformer faults (such as winding deformation), avoiding the influence of impedance characteristic changes caused by non-internal transformer faults on subsequent algorithms' judgment of the transformer condition, thus ensuring the accuracy of monitoring and fault diagnosis results. Similarly, step A5 mathematically eliminates invalid data to ensure the purity of the final impedance matrix data. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for generating impedance matrix data of a transformer, which is one embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of an impedance detection system according to one embodiment of the present invention.

[0019] The components include: 1. Wideband frequency response detection equipment; 2. Data host; 3. Voltage transformer; 4. Current transformer; 5. Port; and 6. Detection sensor. Detailed Implementation

[0020] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0021] In the description of embodiments of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of embodiments of the present invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention according to the specific circumstances.

[0023] The following is combined Figures 1 to 2 This invention describes a method for generating impedance matrix data of a transformer and an impedance detection system according to an embodiment of the present invention.

[0024] Example 1 A method for generating impedance matrix data of a transformer includes the following steps: A1: When the output signals of voltage transformers and current transformers on multiple ports of the transformer are detected, the online voltage signal and online current signal of each port of the transformer are synchronously collected through the voltage transformers and current transformers respectively, and then step A2 is executed; otherwise, step A3 is executed. A2: Based on the specific frequency of transformer operation, calculate the online impedance vector of each port and the online mutual impedance between the port and other ports by collecting the online voltage and online current signals from each port. Then, concatenate all online mutual impedances at the same frequency into an online impedance matrix and proceed to step A4. A3: Actively inject multiple frequency signals into multiple ports of the transformer using a wideband frequency response detection device, wait for the response, and obtain offline voltage and offline current signals; calculate the offline impedance vector of each port and the offline mutual impedance between the port and other ports from the offline voltage and offline current signals of each port, and splice all offline mutual impedances at the same frequency point into an offline impedance matrix, and then execute step A4. A4: Based on at least one externally influencing physical quantity, normalize the online impedance matrix and the offline impedance matrix respectively, and calculate the condition number for each online impedance matrix and each offline impedance matrix, and then proceed to step A5; A5: When the condition number of an online impedance matrix or offline impedance matrix exceeds a preset threshold, the corresponding online impedance matrix or offline impedance matrix is ​​invalidated, and all other online impedance matrices and offline impedance matrices are valid data.

[0025] In a preferred embodiment of the method for generating impedance matrix data of a transformer proposed in this invention, such as... Figure 1 As shown, first execute step A1 to see if the data host can obtain signals from the voltage transformers and current transformers at multiple ports of the transformer. If so, it proves that the transformer is currently running and is in an online state; otherwise, the transformer is in an offline state. If it is in an online state (step A2), then calculate the online impedance matrix obtained at specific frequency points (such as the fundamental frequency 50Hz / 60Hz and specific harmonics with significant energy: 2nd harmonic 100Hz, 3rd harmonic 150Hz, 5th harmonic 250Hz, etc.) when the transformer is running. If it is in an offline state (step A3), then actively inject multiple frequency signals into multiple ports of the transformer through a broadband frequency response detection device to calculate the offline impedance matrix at more frequency points. The combination of online and offline impedance matrix data reflects the condition of the transformer more comprehensively, avoiding omissions in monitoring and fault diagnosis.

[0026] Meanwhile, regardless of whether online or offline detection is performed, the resulting matrix data is affected by the current transformer condition. For example, changes in oil temperature can cause slight thermal expansion and contraction of windings and structural components, leading to minor changes in leakage inductance. If this is not eliminated, it will affect the accuracy of the matrix data. Therefore, based on the physical quantities affected by external factors on the transformer (selected according to the actual situation), the matrix is ​​normalized (i.e., step A4) to optimize the data. This allows the focus to be placed on changes in intrinsic impedance characteristics caused by internal transformer faults (such as winding deformation), avoiding the influence of impedance characteristic changes caused by non-internal transformer faults on subsequent algorithms' judgment of the transformer condition, thus ensuring the accuracy of monitoring and fault diagnosis results. Similarly, step A5 mathematically eliminates invalid data to ensure the purity of the final impedance matrix data.

[0027] It should be noted that, taking a transformer with three ports—high-voltage side, low-voltage side, and neutral point—as an example, for each measurement frequency point... (Whether it's a swept frequency point or an actual harmonic point), calculate its corresponding impedance matrix Z( For a three-port network, its online or offline impedance matrix is ​​in the form of:

[0028] Wherein, matrix element Z ij (f k(H represents the high-voltage side port of the transformer, L represents the low-voltage side port of the transformer, N represents the neutral point port of the transformer, and i and j represent the row and column respectively.) The meaning of Z is: ij (f k )=V i (f k ) / I j (f k ), at frequency f k The mutual impedance seen from port i when current is injected only at port j (or other ports are open).

[0029] Furthermore, the online impedance vector and offline impedance vector represent the self-impedance of the port. The online mutual impedance calculation method for each port to all other ports is the commonly used coupling coefficient method (existing technology, not elaborated here), and the coupling coefficient is selected based on actual verification. All mutual impedances of each port at the same frequency can be referenced to the above matrix form; for example, for port H, then Z... HH (f k Z HL (f k ) and Z HN (f k ).

[0030] Furthermore, step A4 includes the following sub-steps: A41: Based on the top oil temperature of the transformer, the online impedance matrix and the offline impedance matrix are normalized for the first time. A42: Based on the load current of the transformer, the online impedance matrix and the offline impedance matrix are normalized a second time. A43: Calculate the condition numbers for the online impedance matrix and the offline impedance matrix after the second normalization process.

[0031] In this embodiment, considering that oil temperature changes can cause slight thermal expansion and contraction of windings and structural components, resulting in minor changes in leakage inductance, a first normalization process is performed based on the transformer's top-layer oil temperature (normalization eliminates changes caused by external operating conditions, thus highlighting changes in intrinsic parameters caused by changes in the transformer's internal state, such as faults or aging). It is also considered that under heavy load, large transformers experience a temperature rise in the windings due to Joule heating from the current (hot spot temperature), leading to changes in resistance. This change is transient, unlike the slow change in top-layer oil temperature; therefore, based on the oil temperature normalization (i.e., eliminating the influence of oil temperature), further load current normalization is performed.

[0032] It is important to note that the condition number calculation in sub-step A43 is the mathematical calculation of the condition number of a matrix. For example, for the impedance matrix Z, its condition number is cond(Z). The specific formula and calculation process can be found in the condition number calculation formula documentation. In the context of a transformer impedance matrix: (1) Small condition number (close to 1): This indicates that the matrix is ​​"well-formed", the impedance relationship between each port is relatively independent, and the measurement results are stable and reliable, which corresponds to the normal operating state of the transformer.

[0033] (2) Large condition number (far greater than 1, such as greater than 10 to the power of 6): indicates that the matrix is ​​"ill-conditioned". There is an approximate linear correlation between the rows or columns of the matrix. Small measurement errors (noise) can cause huge fluctuations in the impedance calculation results, which usually indicates that the data has extreme conditions.

[0034] Furthermore, sub-step A41 includes: The formula for the first normalization process is: ; k R =(C ref +235)\( C oil +235); k X =1; in: This refers to the online or offline impedance matrix after the first normalization process. The online or offline impedance matrix before the first normalization process, k R k is the resistance normalization factor. X C is the reactance normalization factor. ref As the reference temperature value, C oil This refers to the top oil temperature value. The online impedance matrix and the offline impedance matrix are normalized for the first time using the first normalization formula.

[0035] In this embodiment, the oil temperature normalization principle is as follows: the winding resistance R has a linear relationship with temperature, R∝(T+235) (for copper windings), thus the resistance normalization factor k is derived. R Since reactance X is theoretically independent of temperature, the reactance normalization factor k is derived. X , is a coefficient that is approximately 1.

[0036] Furthermore, sub-step A42 includes: The formula for the second normalization process is: ; in: The resistance after the second normalization process. The resistance after the first normalization process. This is the rated load current. For load current, Custom calculation factors; The resistance of each online impedance vector in the online impedance matrix is ​​normalized a second time using the second normalization formula, and the resistance of each offline impedance vector in the offline impedance matrix is ​​normalized a second time using the second normalization formula.

[0037] In this embodiment, based on the normalization of oil temperature, the resistance is further compensated for by load current, i.e., R in the impedance vector Z=R+jX (online or offline).

[0038] It should be noted that, The custom calculation factor can be a hotspot-based factor used to compensate for winding temperature rise caused by load current variations. For the initial model, it can be simplified to... =1.

[0039] Furthermore, in step A2, the online voltage signal and online current signal acquired at each port are used to calculate the online impedance vector of that port through a synchronous lock-in amplifier.

[0040] In this embodiment, the signal processing principle of the synchronous lock-in amplifier is as follows: (1) The online voltage signal and the online current signal are multiplied by a sinusoidal reference signal and a cosine reference signal of the same frequency (such as the fundamental frequency of 50Hz, the second harmonic of 100Hz, etc.).

[0041] (2) Low-pass filtering extraction: The multiplied signal contains high-frequency components and low-frequency (DC) components; by using a low-pass filter, high-frequency noise can be filtered out, and only the low-frequency components related to the reference signal are retained. The magnitude of this low-frequency component is directly proportional to the amplitude of the component in the original voltage signal that is in phase and has the same frequency as the reference signal.

[0042] (3) Phase information acquisition: Lock-in amplifiers can usually also provide signals with a fixed phase difference from the reference signal (such as quadrature signals). By comparing the magnitudes of the in-phase and quadrature components, the phase angle of the signal can be calculated.

[0043] (4) Given the amplitude and phase angle, the resistance component (R, real part) and reactance component (X, imaginary part) can be obtained, and the online impedance vector can be obtained from Z=R+jX.

[0044] Step A2 performs online impedance vector calculation using a synchronous lock-in amplifier, which can greatly suppress noise at non-measured frequencies, accurately extract specific frequencies (such as the power frequency fundamental wave and specific harmonics with significant energy), and has a high signal-to-noise ratio. It is preferred for processing detection data during normal transformer operation (i.e., online).

[0045] Furthermore, in step A3, the broadband frequency response testing equipment uses a frequency response analyzer.

[0046] In this embodiment, the frequency response analyzer (FRA) can perform active frequency sweep measurements (i.e., multiple frequency signals) over a wide bandwidth (e.g., 1kHz to 2MHz). For example, while injecting a sinusoidal frequency sweep current signal into the port, the voltage response can be measured at the port, thereby obtaining a wideband offline voltage signal and offline current signal, and subsequently calculating the offline impedance vector.

[0047] Furthermore, in step A3, the offline voltage signal and offline current signal of each port are first denoised using the wavelet thresholding method, and then the offline impedance vector of that port is calculated.

[0048] In this embodiment, the wideband scanning data from the frequency response analyzer (FRA) contains random noise and local impulse interference throughout the entire frequency band. Therefore, it is preferable to denoise the offline voltage and current signals before calculation. More importantly, the heuristic threshold of the wavelet thresholding method can be adaptively calculated by the computer, which can effectively remove noise while retaining key abrupt changes in the impedance frequency response curve (these points may correspond to the resonant frequency of the winding and are important fault characteristics).

[0049] Furthermore, in step A3, the offline voltage signal and offline current signal of each port are used to calculate the offline impedance vector of that port through Fourier transform.

[0050] In this embodiment, since the impedance detection is performed while the transformer is offline, and the noise has been reduced by wavelet thresholding, the offline voltage and current signals have less noise. In addition, since there is a large amount of wideband data, Fourier transform (FFT) is preferred to calculate the offline impedance vector, which can quickly process a large amount of data.

[0051] Example 2 An impedance detection system includes a broadband frequency response detection device 1, a data host 2, multiple voltage transformers 3, multiple current transformers 4, and at least one detection sensor 6; the voltage transformers 3 and current transformers 4 are electrically connected to the ports 5 of the transformers respectively, the ports 5 of the transformers are all electrically connected to the broadband frequency response detection device 1, and the detection sensor 6, the broadband frequency response detection device 1, the voltage transformers 3 and the current transformers 4 are all electrically connected to the data host 2; Sensor 6 is used to detect physical quantities affected by external factors; Data host 2 executes a program according to the above-mentioned method for generating impedance matrix data of a transformer to generate impedance matrix data.

[0052] In this embodiment, a preferred embodiment of the impedance detection system is also proposed, such as... Figure 2As shown, the wideband frequency response detection device 1 is used to perform the detection in step A1, the voltage transformer 3 and the current transformer 4 are used to perform the detection in step A3, the detection sensor 6 is used to perform the detection in step A4, and the remaining steps are processed by the data host 2, finally obtaining the impedance matrix data composed of the effective online impedance matrix and the offline impedance matrix.

[0053] It should be noted that the selection of sensor 6 depends on the external influencing physical quantity in step A4; for example, if the top oil temperature and load current are external influencing physical quantities in step A4, then a sensor capable of detecting the top oil temperature and load current can be added and connected to the data host.

[0054] The other components and operation of the transformer impedance matrix data generation method and impedance detection system according to the embodiments of the present invention are known to those skilled in the art and will not be described in detail here.

[0055] In the description of this specification, references to terms such as "embodiment," "example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0056] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for generating impedance matrix data of a transformer, characterized in that: The method comprises the following steps: A1: when the output signals of the voltage and current transformers on the multiple ports of the transformer are detected, the online voltage and current signals of each port of the transformer are synchronously collected by the voltage and current transformers respectively, and then step A2 is performed; Otherwise, step A3 is performed; A2: according to the specific frequency point of the transformer operation, the online impedance vector of each port and the online mutual impedance between the port and each port are calculated according to the online voltage and current signals collected by each port, and all the online mutual impedances at the same frequency point are spliced into an online impedance matrix, and then step A4 is performed; A3: a wideband frequency response detection device actively injects multiple frequency signals into the multiple ports of the transformer, and waits for the response to obtain offline voltage and current signals; The offline impedance vector of each port and the offline mutual impedance between the port and each port are calculated according to the offline voltage and current signals of each port, and all the offline mutual impedances at the same frequency point are spliced into an offline impedance matrix, and then step A4 is performed; A4: based on at least one external influence physical quantity, the online impedance matrix and the offline impedance matrix are normalized respectively, and the condition number of each online impedance matrix and each offline impedance matrix is calculated, and then step A5 is performed; A5: when the condition number of the online impedance matrix or the offline impedance matrix is greater than a preset threshold, the corresponding online impedance matrix or offline impedance matrix is invalid, and the remaining online impedance matrix and offline impedance matrix are valid data.

2. The method of claim 1, wherein: The step A4 comprises the following sub-steps: A41: based on the top oil temperature of the transformer, the online impedance matrix and the offline impedance matrix are subjected to first normalization processing respectively; A42: based on the load current of the transformer, the online impedance matrix and the offline impedance matrix are subjected to second normalization processing respectively; A43: the condition number of the online impedance matrix and the offline impedance matrix after the second normalization processing is calculated.

3. The method of claim 2, wherein: The sub-step A41 comprises: The first normalization processing formula is: ； k R = (C ref + 235) (C oil + 235); k X =1； wherein: is the online impedance matrix or offline impedance matrix after the first normalization process, is the online impedance matrix or offline impedance matrix before the first normalization process, k R is the resistance normalization factor, k X is the reactance normalization factor, C ref is the reference temperature value, C oil is the top layer oil temperature value; The online impedance matrix and the offline impedance matrix are subjected to first normalization processing respectively by using the first normalization processing formula.

4. The method of claim 2, wherein: The sub-step A42 comprises: The second normalization processing formula is: ； wherein: is the resistance after the second normalization process, is the resistance after the first normalization process, is the rated load current, is the load current, is a self-defined calculation factor; The resistance of each online impedance vector in the online impedance matrix is subjected to second normalization processing by using the second normalization processing formula, and the resistance of each offline impedance vector in the offline impedance matrix is subjected to second normalization processing by using the second normalization processing formula.

5. The method of claim 1, wherein: In the step A2, the online voltage and current signals collected by each port are calculated into the online impedance vector of the port by a synchronous phase-locked amplifier.

6. The method of claim 1, wherein: In the step A3, the wideband frequency response detection device uses a frequency response analyzer.

7. The method of claim 1, wherein: In the step A3, the offline voltage and current signals of each port are first denoised by a wavelet threshold method, and then the offline impedance vector of the port is calculated.

8. The method of claim 1, wherein: In the step A3, the offline voltage and current signals of each port are calculated into the offline impedance vector of the port by Fourier transform.

9. An impedance detection system characterized by: The wideband frequency response detection device, the data host, a plurality of voltage transformers, a plurality of current transformers and at least one detection sensor are included; the voltage transformers and the current transformers are respectively and one by one electrically connected with the ports of the transformer, the ports of the transformer are electrically connected with the wideband frequency response detection device, and the detection sensor, the wideband frequency response detection device, the voltage transformers and the current transformers are electrically connected with the data host; The detection sensor is used for detecting external influence physical quantity; The data host executes a program according to the transformer impedance matrix data generation method in any one of claims 1 to 8 to generate impedance matrix data.

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