灰色关联分析在变压器DGA缺码数据中的应用研究Application Research of Grey Relational Analysis in Transformer DGA Code Absence Data

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Three-ratio method is one of the effective methods for latent fault diagnosis of power transfor-mers, but there is a lack of code in this method. According to the DGA data collected in this paper, it is found that the variation trend of the characteristic gas in the same fault samples is the same, and the variation trend of different fault features is obviously different. In this paper, by excavate the changing trend of each data in DGA, using the grey relational theory and using the DGA fault identification method based on grey relational analysis, the fault diagnosis of code absence power transformers in DGA is carried out. It makes up for the deficiency of the three ratio method and improves the accuracy of transformer fault diagnosis. The research results have important theoretical value and practical value of engineering. It can be popularized vigorously and bring great economic benefits to the power system and the society.

1. 引言

2. 故障气体规律

Table 1. Data and fault type of the code 012 (uL/L)

Figure 1. Data of the code 012

3. 灰色关联度方法简介

${X}_{i}=\left({x}_{i}\left(1\right),{x}_{i}\left(2\right),\cdots ,{x}_{i}\left(n\right)\right)$$i=0,1,2,\cdots ,m$

$\gamma \left({x}_{0}\left(k\right),{x}_{i}\left(k\right)\right)=\frac{\underset{i}{\mathrm{min}}\underset{k}{\mathrm{min}}{\Delta }_{0i}\left(k\right)+\xi \underset{i}{\mathrm{max}}\underset{k}{\mathrm{max}}{\Delta }_{0i}\left(k\right)}{{\Delta }_{0i}\left(k\right)+\xi \underset{i}{\mathrm{max}}\underset{k}{\mathrm{max}}{\Delta }_{0i}\left(k\right)}$ (1)

${x}_{i}\left(k\right)$${x}_{0}\left(k\right)$ 的关联度系数， ${\Delta }_{0i}\left(k\right)$${x}_{i}\left(k\right)$${x}_{0}\left(k\right)$ 两点之间的绝对差， ${\Delta }_{0i}\left(k\right)=|{x}_{0}\left(k\right)-{x}_{i}\left(k\right)|$ $\xi \in \left[0,1\right]$ 为分辨系数。

$\gamma \left({x}_{0},{x}_{i}\right)=\frac{1}{n}\underset{k=1}{\overset{n}{\sum }}\gamma \left({x}_{0}\left(k\right),{x}_{i}\left(k\right)\right),k=0,1,2,\cdots ,n$ (2)

4. 故障诊断方法应用步骤

Table 2. The proportion of fault gases

Table 3. Data and fault type of the code 011 (uL/L)

$\gamma {\left(i\right)}_{\psi }=\frac{1}{n-1}\underset{j=1,j\ne i}{\overset{n-1}{\sum }}\gamma {\left(i,j\right)}_{\psi }$

$\gamma {\left(\zeta \right)}_{\psi }=\frac{1}{n}\underset{i=1}{\overset{n}{\sum }}\gamma {\left(i\right)}_{\psi }$

$\gamma \left(\zeta \right)=1-\frac{1}{5}\underset{\psi }{\sum }|\gamma {\left(\zeta \right)}_{\psi }-\gamma {\left(0\right)}_{\psi }|$

5. 实例验证分析

Figure 2. Trend of low temperature overheating fault about code 011 in partial discharge data

Table 4. Fault diagnosis results of the code 000 used by grey relational analysis

6. 结论

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