基于VMD和多尺度熵的变压器内绝缘局部放电信号特征提取及分类

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摘要为了有效提取局部放电信号的特征,提出了一种基于变分模态分解(VMD)和多尺度熵(MSE)的特征向量提取方法,并采用BP神经网络分类器对放电类型进行识别。特征向量的提取过程是首先利用VMD分解算法对局部放电信号进行分解,得到数个有限带宽的固有模态分量;然后分别计算分解得到的模态分量的MSE,将其组合得到初始特征向量;最后利用主成分分析法对初始特征向量进行降维处理。用该方法对实验室条件下4种放电信号和不同放电程度的电晕放电进行特征提取及识别。结果表明,该方法能有效提取放电信号的特征,以其作为特征向量可以正确识别不同的放电类型和同种放电类型下的不同放电程度。

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	贾亚飞
	朱永利
	王刘旺
	李莉

关键词 ：局部放电, 变分模态分解, 多尺度熵, 特征提取, 模式识别

Abstract：In order to extract features of partial discharge signals effectively,a method based on variational mode decomposition (VMD) and multiscale entropy (MSE) is proposed for extracting feature vectors,and the back-propagation neural networks is utilized to recognize the discharge types.First of all,the known partial discharge signals are decomposed by VMD and several band-limited intrinsic mode functions (BLIMFs) are extracted.Then the MSE of each intrinsic mode is calculated respectively and the initial feature vector can be acquired by the combination of the MSEs.Finally,the dimension reduction of the feature vectors is carried out by the principal component analysis (PCA).Four types of discharge signals and different degree of corona discharge signals within each discharge type are extracted and recognized using the above methods.Simulation results demonstrate that the proposed method can extract the features of partial discharge signals effectively.With the results as characteristics,it can correctly identify different discharge types and characteristics of the same discharge types under different discharge levels.

Key words： Partial discharge variational mode decomposition multiscale entropy feature extraction pattern recognition

收稿日期: 2015-06-10 出版日期: 2016-11-02

PACS:

TM85

基金资助:国家电网公司科技项目资助。

作者简介: 贾亚飞女,1988年生,博士研究生,高压设备局部放电信号分析与故障诊断。E-mail:jiayafeiyanshan@163.com朱永利男,1963年生,教授,博士生导师,研究方向为网络化监控与智能信息处理研究。E-mail:yonglipw@163.com(通信作者)

引用本文:

贾亚飞,朱永利,王刘旺,李莉. 基于VMD和多尺度熵的变压器内绝缘局部放电信号特征提取及分类[J]. 电工技术学报, 2016, 31(19): 208-217. Jia Yafei, Zhu Yongli, Wang Liuwang, Li Li. Feature Extraction and Classification on Partial Discharge Signals of Power Transformers Based on VMD and Multiscale Entropy. Transactions of China Electrotechnical Society, 2016, 31(19): 208-217.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I19/208

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