CN106338237A - Transformer winding deformation detection method based on frequency response impedance method - Google Patents

Abstract

The invention relates to a transformer winding deformation detection method based on a frequency response impedance method, comprising the following steps: using the frequency response method to measure the voltage and current signals at the response end and the excitation end of the transformer winding to be detected; using the measured data to calculate the winding to be detected Impedance values at different frequencies; use the impedance data of the winding to be tested and its normal impedance data to draw the frequency response impedance curve in the low frequency band (10-1000Hz) and the middle frequency band (1-45kHz); use the obtained impedance data to calculate The correlation coefficient of the two curves can be used to judge the deformation of the winding. The present invention utilizes the connection mode of the frequency response method to obtain other criteria for diagnosing the deformation of the transformer winding, which can be referred to each other with the diagnosis result of the frequency response method, thereby improving the correct rate of diagnosis of the transformer winding deformation.

Description

Transformer Winding Deformation Detection Method Based on Frequency Response Impedance Method

technical field

The invention belongs to the technical field of electric equipment fault diagnosis, and in particular relates to a transformer winding deformation detection method based on a frequency response impedance method.

Background technique

Transformer is an important electrical equipment in the power system. It plays an important role in energy distribution and voltage level conversion in the power system. Its operational reliability is an important guarantee for the stable and safe operation of the power system. The statistical results of actual operation show that winding deformation is one of the most common faults of transformers. Reliable and accurate detection of transformer winding deformation is of great significance to reduce the accident rate of power transformers and ensure the safe operation of transformers.

The frequency response method is one of the most important methods to detect transformer winding deformation at home and abroad. When the excitation signal frequency is higher than 1kHz, the transformer winding can be equivalent to a passive linear network, and the frequency response characteristic is a prominent property of this passive linear network. For a certain transformer, its frequency response characteristic is unique. When the transformer winding is deformed due to some kind of fault, the frequency response characteristic of its winding equivalent network will also change accordingly. When using the frequency response method for testing, a sinusoidal frequency sweep signal is applied to one side of the transformer winding, and the response signal of the sweep signal is collected on the other side of the winding, and then the frequency response curve of the winding is obtained through processing, and the fault is analyzed by comparison The difference between the frequency response curves of the front and rear windings is used to judge the deformation of the windings.

In the actual test, due to the interference of the electromagnetic signal on site, the influence of the length of the lead wire, the position of the ground point, and the contact resistance of the test fixture on the test results, the test data has poor repeatability, distortion, and even misjudgment of the winding deformation. Therefore, it is of great practical significance to study a new transformer winding fault judgment method using the wiring method of the frequency response method as a mutual reference with the diagnosis results of the frequency response method.

Contents of the invention

The purpose of the present invention is to provide a transformer winding deformation detection method based on the frequency response impedance method, using the connection mode of the frequency response method to obtain other criteria for diagnosing the transformer winding deformation through this method, which is mutually correlated with the diagnostic results of the frequency response method For reference, improve the correct rate of transformer winding deformation diagnosis.

The technical solution of the present invention is a transformer winding deformation detection method based on the frequency response impedance method, which specifically includes the following steps:

Step 1: Select the transformer winding to be tested, apply a sinusoidal frequency sweep signal U _S at one end, measure the response terminal voltage U ₂ (f), excitation terminal voltage U ₁ (f) and the current flowing through the winding at different frequencies I(f).

Step 2: For the voltage and current signals collected in the above step 1, the impedance values Z(f) at different frequencies are obtained through data processing.

Step 3: For the impedance calculated in step 2, draw a frequency response impedance curve for the low frequency band (10~1000Hz) and the middle frequency band (1~45kHz), where the abscissa is the frequency f, and the ordinate is the corresponding impedance value. In the same way, the frequency response impedance curve of the transformer winding is drawn in the same coordinate system.

Step 4: For the curve data obtained in step 3, use the correlation coefficient method to define the similarity of the two curves, and judge the winding deformation according to the similarity.

In the step 2, the following steps are specifically included:

Step 21: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 10-1000Hz, according to the formula $\stackrel{\&Right\; Arrow;}{Z}\left(f\right)=\left(\frac{{\stackrel{\&Right\; Arrow;}{u}}_i\left(f\right)-{\stackrel{\&Right\; Arrow;}{u}}_o\left(f\right)}{\stackrel{\&Right\; Arrow;}{I}\left(f\right)}\right)=R\left(f\right)+\mathrm{wxya}\left(f\right)$ and $\left|\stackrel{\&Right\; Arrow;}{Z}\left(f\right)\right|=\sqrt{R^2\left(f\right)+x^2\left(f\right)}$ Calculate the impedance value for the mid-band.

Step 22: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 1-45kHz, according to the formula $h\left(f\right)=20\log \sqrt{R^2\left(f\right)+x^2\left(f\right)}=20\log \left(\right|\stackrel{\&Right\; Arrow;}{Z}\left(f\right)\left|\right)$ Calculate the impedance value for the mid-band.

In the step 4, the following steps are specifically included:

Step 41: For the curve data obtained in step 2, assume that it is two amplitude sequences X(i), Y(i) whose length is N, i=0, 1, ..., N-1, and X( i), Y(i) are real numbers. Computes the standard deviation of two series, where ${\mathrm{\σ}}_x=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{x}_i]}^2,{\mathrm{\σ}}_{\mathrm{the\; y}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\mathrm{the\; y}}_i]}^2.$

Step 42: For the two magnitude sequences in step 41, calculate the covariance of the two sequences $C_{\mathrm{xy}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{x}_i]\×[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\mathrm{the\; y}}_i].$

Step 43: For the two amplitude sequences in step 41, use the standard variance in step 41 and the covariance in step 42 to normalize the covariance of the two sequences

Step 44: For the normalized covariance LR _xy in step 43, if 1-LR _xy <10 ^-10 , then the correlation coefficient R _xy is 10; if 1-LR _xy ≥10 ^-10 , then the correlation coefficient R _xy =-lg(1-LR _xy ).

Step 45: For the correlation coefficient R _xy of step 44, if R _xy <0.6, it is determined that the transformer winding is seriously deformed; if 0.6≤R _xy <1, it is determined that the transformer winding is obviously deformed; if R _xy ≥ 1, the winding normal.

The transformer winding deformation detection method based on the frequency response impedance method provided by the present invention uses the connection method of the frequency response method to obtain other criteria for diagnosing the transformer winding deformation through this method, and the diagnostic results of the frequency response method can be used as a mutual reference to improve the efficiency of the transformer. The correct rate of winding deformation diagnosis.

Description of drawings

Fig. 1 is the flowchart of the transformer winding deformation detection method based on the frequency response impedance method of the present invention;

Fig. 2 is the flow chart of calculating the impedance value under different frequencies described in step 2 of the present invention;

Fig. 3 is the flowchart of the method for calculating the correlation coefficient of the frequency response impedance curve described in step 4 of the present invention;

detailed description

A preferred embodiment of the present invention will be specifically described below with reference to FIGS. 1 to 3 . It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

As shown in FIG. 1 , the transformer winding deformation detection method based on the frequency response impedance method provided by the present invention specifically includes the following steps.

Step 1: Select the transformer winding to be tested, apply a sinusoidal frequency sweep signal U _S at one end, measure the response terminal voltage U ₂ (f), excitation terminal voltage U ₁ (f) and the current flowing through the winding at different frequencies I(f).

Step 2: For the voltage and current signals collected in the above step 1, the impedance values Z(f) at different frequencies are obtained through data processing.

Step 21: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 10-1000Hz, according to the formula $\stackrel{\&Right\; Arrow;}{Z}\left(f\right)=\left(\frac{{\stackrel{\&Right\; Arrow;}{u}}_i\left(f\right)-{\stackrel{\&Right\; Arrow;}{u}}_o\left(f\right)}{\stackrel{\&Right\; Arrow;}{I}\left(f\right)}\right)=R\left(f\right)+\mathrm{wxya}\left(f\right)$ and $\left|\stackrel{\&Right\; Arrow;}{Z}\left(f\right)\right|=\sqrt{R^2\left(f\right)+x^2\left(f\right)}$ Calculate the impedance value for the mid-band.

Step 22: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 1-45kHz, according to the formula $h\left(f\right)=20\log \sqrt{R^2\left(f\right)+x^2\left(f\right)}=20\log \left(\right|\stackrel{\&Right\; Arrow;}{Z}\left(f\right)\left|\right)$ Calculate the impedance value for the mid-band.

Step 3: For the impedance calculated in step 2, draw a frequency response impedance curve for the low frequency band (10~1000Hz) and the middle frequency band (1~45kHz), where the abscissa is the frequency f, and the ordinate is the corresponding impedance value. In the same way, the frequency response impedance curve of the transformer winding is drawn in the same coordinate system.

Step 4: For the curve data obtained in step 3, use the correlation coefficient method to define the similarity of the two curves, and judge the winding deformation according to the similarity.

Step 41: For the curve data obtained in step 2, assume that it is two amplitude sequences X(i), Y(i) whose length is N, i=0, 1, ..., N-1, and X( i), Y(i) are real numbers. Computes the standard deviation of two series, where ${\mathrm{\&sigma;}}_x=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x}_i]}^2,{\mathrm{\&sigma;}}_{\mathrm{the\; y}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{the\; y}}_i]}^2.$

Step 42: For the two magnitude sequences in step 41, calculate the covariance of the two sequences $C_{\mathrm{xy}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x}_i]\&times;[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{the\; y}}_i].$

Step 43: For the two amplitude sequences in step 41, use the standard variance in step 41 and the covariance in step 42 to normalize the covariance of the two sequences

Step 44: For the normalized covariance LR _xy in step 43, if 1-LR _xy <10 ^-10 , then the correlation coefficient R _xy is 10; if 1-LR _xy ≥10 ^-10 , then the correlation coefficient R _xy =-lg(1-LR _xy ).

Step 45: For the correlation coefficient R _xy of step 44, if R _xy <0.6, it is determined that the transformer winding is seriously deformed; if 0.6≤R _xy <1, it is determined that the transformer winding is obviously deformed; if R _xy ≥ 1, the winding normal.

Although the content of the present invention has been described in detail through the above preferred embodiments, it should be understood that the above description should not be considered as limiting the present invention. Various modifications and alterations to the present invention will become apparent to those skilled in the art upon reading the above disclosure. Therefore, the protection scope of the present invention should be defined by the appended claims.

Claims (3)

1. based on the transformer winding deformation detection method of frequency response impedance method, it is characterized in that, described method comprises the following steps: Step 1: Select the transformer winding to be tested, apply a sinusoidal frequency sweep signal U _S at one end, measure the response terminal voltage U ₂ (f), excitation terminal voltage U ₁ (f) and the current flowing through the winding at different frequencies I(f). Step 2: For the voltage and current signals collected in the above step 1, the impedance values Z(f) at different frequencies are obtained through data processing. Step 3: For the impedance calculated in step 2, draw a frequency response impedance curve for the low frequency band (10~1000Hz) and the middle frequency band (1~45kHz), where the abscissa is the frequency f, and the ordinate is the corresponding impedance value. In the same way, the frequency response impedance curve of the transformer winding is drawn in the same coordinate system. Step 4: For the curve data obtained in step 3, use the correlation coefficient method to define the similarity of the two curves, and judge the winding deformation according to the similarity. 2. the transformer winding deformation detection method based on frequency response impedance method as claimed in claim 1, is characterized in that, in described step 2, specifically comprises the following steps: Step 21: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 10-1000Hz, according to the formula $\stackrel{\&Right\; Arrow;}{Z}\left(f\right)=\left(\frac{{\stackrel{\&Right\; Arrow;}{u}}_i\left(f\right)-{\stackrel{\&Right\; Arrow;}{u}}_o\left(f\right)}{\stackrel{\&Right\; Arrow;}{I}\left(f\right)}\right)=R\left(f\right)+\mathrm{wxya}\left(f\right)$ and $\left|\stackrel{\&Right\; Arrow;}{Z}\left(f\right)\right|=\sqrt{R^2\left(f\right)+x^2\left(f\right)}$ Calculate the impedance value for the mid-band. Step 22: For the voltage and current signals measured in step 1, for the data measured in the frequency range of 1-45kHz, according to the formula Calculate the impedance value for the mid-band. 3. the transformer winding deformation detection method based on frequency response impedance method as claimed in claim 1, is characterized in that, in described step 4, specifically comprises the following steps: Step 41: For the curve data obtained in step 2, assume that it is two amplitude sequences X(i), Y(i) whose length is N, i=0, 1, ..., N-1, and X( i), Y(i) are real numbers. Computes the standard deviation of two series, where ${\mathrm{\&sigma;}}_x=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x}_i{]}^2,$ ${\mathrm{\&sigma;}}_{\mathrm{the\; y}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{the\; y}}_i{]}^2.$ Step 42: For the two magnitude sequences in step 41, calculate the covariance of the two sequences $C_{\mathrm{xy}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}[x_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x}_i]\&times;[{\mathrm{the\; y}}_i-\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{the\; y}}_i].$ Step 43: For the two amplitude sequences in step 41, use the standard variance in step 41 and the covariance in step 42 to normalize the covariance of the two sequences ${\mathrm{LR}}_{\mathrm{xy}}=C_{\mathrm{xy}}/\sqrt{{\mathrm{\&sigma;}}_x{\mathrm{\&sigma;}}_{\mathrm{the\; y}}}.$ Step 44: For the normalized covariance LR _xy in step 43, if 1-LR _xy <10 ^-10 , then the correlation coefficient R _xy is 10; if 1-LR _xy ≥10 ^-10 , then the correlation coefficient R _xy =-1g(1-LR _xy ). Step 45: For the correlation coefficient R _xy of step 44, if R _xy <0.6, it is determined that the transformer winding is seriously deformed; if 0.6≤R _xy <1, it is determined that the transformer winding is obviously deformed; if R _xy ≥ 1, the winding normal.