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Analysis of characteristic difference index of transformer winding frequency response fingerprint

Analysis of characteristic difference index of transformer winding frequency response fingerprint

(Summary description)Transformer is the key equipment for power transmission and transformation in the power system, and its safe and stable operation is of great significance to ensure the reliability of the power system. After the transformer suffers from a sudden short-circuit in the near area, the winding may be deformed. It is necessary to do a winding deformation test to determine that the transformer is free of faults before it can be put into operation.
The detection of transformer winding deformation by frequency response analysis has the advantages of high sensitivity and convenient on-site use, and has been widely used in the power industry. But for a long time, the use of frequency response analysis method to diagnose transformer winding deformation is mainly based on the basis of comparing frequency response fingerprints through experience, lacking in-depth data analysis methods.

Analysis of characteristic difference index of transformer winding frequency response fingerprint

(Summary description)Transformer is the key equipment for power transmission and transformation in the power system, and its safe and stable operation is of great significance to ensure the reliability of the power system. After the transformer suffers from a sudden short-circuit in the near area, the winding may be deformed. It is necessary to do a winding deformation test to determine that the transformer is free of faults before it can be put into operation.
The detection of transformer winding deformation by frequency response analysis has the advantages of high sensitivity and convenient on-site use, and has been widely used in the power industry. But for a long time, the use of frequency response analysis method to diagnose transformer winding deformation is mainly based on the basis of comparing frequency response fingerprints through experience, lacking in-depth data analysis methods.

Information

Transformer is the key equipment for power transmission and transformation in the power system, and its safe and stable operation is of great significance to ensure the reliability of the power system. After the transformer suffers from a sudden short-circuit in the near area, the winding may be deformed. It is necessary to do a winding deformation test to determine that the transformer is free of faults before it can be put into operation.
The detection of transformer winding deformation by frequency response analysis has the advantages of high sensitivity and convenient on-site use, and has been widely used in the power industry. But for a long time, the use of frequency response analysis method to diagnose transformer winding deformation is mainly based on the basis of comparing frequency response fingerprints through experience, lacking in-depth data analysis methods.
A sine wave voltage U1 with variable frequency is applied to one end of the winding, and the other end of the winding is connected to a resistor in series and then grounded. Under the excitation of the voltage source, a voltage U2 will be generated on the resistor. The curve of H(f) = 20ln(U2/U1) with frequency (usually 1 kHz~1 MHz) is called frequency response fingerprint (referred to as frequency response fingerprint). The frequency response fingerprint is the basis for the frequency response analysis method to judge the winding deformation. At present, there are three main analysis methods of the frequency response fingerprint: 1) the empirical judgment method; 2) the correlation coefficient method; 3) the difference method. The three methods all judge the winding deformation by analyzing the difference between the frequency response fingerprints.
The empirical judgment method is a method for transformer professionals to judge whether the winding is deformed according to the change of frequency and amplitude at the extreme point of the frequency response fingerprint based on past experience. For experienced professionals, it can more accurately judge whether the winding is deformed. However, this purely empirical method has obvious shortcomings: 1) The experience requirements of analysts are relatively high, and it is difficult to be competent without experience or lack of experience; 2) Due to the dispersion and uncertainty of experience, it is difficult to standardize and generalize. The analysts may come to different analysis conclusions, which brings certain difficulties to the maintenance decision.
The correlation coefficient method judges whether the winding is deformed by the correlation coefficient of the two frequency response fingerprint data sequences. The calculation formula of the correlation coefficient Rxy is:

1

  式中σ xy 为2 个序列的归一化协方差。
  差值法则是通过计算2 个数据序列的差值判断绕组是否发生变形。其中差值的计算公式为:

1

In the formula: E12 is the difference between the two frequency response fingerprint data sequences; n is the number of sampling points; U1n and U2n are the amplitudes of the two sequences at the nth point.
Different from empirical judgment, the correlation coefficient method and the difference method are quantitative analysis methods of frequency response fingerprints. A certain quantitative value is used to characterize the difference between the frequency response fingerprints, and whether the winding is deformed is judged according to the size of the quantitative value. The only advantage of diagnostic results. However, in engineering applications, these two methods are not highly recognized, mainly because: 1) the judgment accuracy is low; 2) the specific changes of frequency and amplitude at the extreme point of the frequency response fingerprint cannot be accurately reflected.
1 Quantitative analysis of differences in fingerprint characteristics
1.1 Fingerprint features and feature points
The fingerprint feature of the frequency response fingerprint is characterized by the amplitude and frequency of all effective extreme points. The so-called effective extreme point refers to the extreme point after omitting the influence of interference, noise, etc., and is abbreviated as feature point for the convenience of description. After the transformer winding is deformed, the fingerprint characteristics of its frequency response fingerprint will change. The analysis of the frequency and amplitude changes of the characteristic points is the key point of empirical judgment of winding deformation. Therefore, the frequency response fingerprint of the winding to be diagnosed can be compared with its original frequency response. Fingerprints (frequency response fingerprints when the windings are not deformed, such as the frequency response fingerprints of the factory test) carry out feature difference analysis to determine whether the windings are deformed. The frequency response fingerprints of the side and in-phase windings are replaced.
In quantitative analysis, extreme points with small changes in adjacent amplitudes are regarded as noise or interference. As shown in Figure 1, if the amplitude difference ΔR between the extreme point a and the adjacent next extreme point b is greater than 0.01R (R is the difference between the maximum and minimum values ​​of the frequency response fingerprint), the extreme The value point a is an effective extreme value point, that is, a characteristic point; otherwise, both a and b are ignored, and then the previous judgment is repeated from the next extreme value point adjacent to b after b. According to this principle, all extreme points are analyzed sequentially from low frequency to high frequency, so as to select all feature points.

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