多尺度熵在变压器振动信号特征提取中的应用
Feature Research of Vibration Signal of Power Transformer Using Multiscale Entropy

以提取变压器绕组振动信号有效特征为目的，对多尺度熵（multiscale entropy, 简称MSE）适用于非平稳非线性振动信号分析的特点和机理进行分析,在此基础上将其引入变压器绕组振动信号的特征提取中。利用不同尺度内信号样本熵的变化来反映变压器绕组运行状态的改变，将其作为一个能定量描述绕组故障信号特征的有效特征参数。实验数据分析表明，与样本熵相比，多尺度熵能更好地实现故障信号特征的定量提取，是表征变压器绕组不同故障信息的一种有效参数。
Multiscale entropy has begun to play an increasingly important role in the analysis of non-stationary and nonlinear vibration signals. Changes in the sample entropy of different scales can reflect changes in the transformer windings of different runnings. In this paper, a novel feature extraction is proposed, and a new and effective feature parameter is provided to efficiently and quantitatively describe faulty signals of the transformer winding. The results of analyzing the experimental data of the winding vibration show that compared to sample entropy, multiscale entropy can efficiently realize the feature extraction of faulty signals. Therefore, it is feasible to introduce the effective feature parameter into the use of transformer winding vibration signal analysis.