基于改进S变换的超高频局部放电信号特征提取及分类  

Feature Extraction and Classification of UHF PD Signals Based on Improved S-Transform

作　　者：龙嘉川 王先培[2] 代荡荡 田猛[2] 朱国威[2] 黄云光 LONG Jiachuan;WANG Xianpei;DAI Dangdang;TIAN Meng;ZHU Guowei;HUANG Yunguang(School of Electronics and Information Engineering,Wuhan Donghu University,Wuhan 430212,China;Electronic Information School,Wuhan University,Wuhan 430072,China;Electric Power Research Institute of Guangxi Power Grid Co.,Ltd.,Nanning 530023,China)

机构地区：[1]武汉东湖学院电子信息工程学院,武汉430212 [2]武汉大学电子信息学院,武汉430072 [3]广西电网有限责任公司电力科学研究院,南宁530023

出　　处：《高电压技术》2018年第11期3649-3656,共8页High Voltage Engineering

基　　金：国家自然科学基金(50677047);武汉东湖学院青年基金(2018dhzk001)~~

摘　　要：超高频（ultra-high frequency, UHF）局部放电（partial discharge, PD）检测法是目前应用最广泛的PD检测方法之一,通过提取UHF PD信号的时频特征可实现PD类型的识别。因此提出了一种基于改进S变换的UHF PD信号时频特征提取方法,首先通过引入新的频域窗宽度计算公式对标准S变换进行改进;然后根据得到的S变换模矩阵计算频率-最大幅值图,并提取出6维统计特征量;最后结合支持向量机（support vector machine, SVM）完成PD信号的识别。试验结果表明：该方法兼顾了S变换的时、频域分辨率,使得到的特征量能更加准确地反映PD成分在时频域的分布特性;在未经去噪的情况下,该方法仍可获得高达97.33%的分类正确率,验证了其较强的噪声鲁棒性;与常用的PD信号特征提取法相比,所提方法获得的PD类型识别率更高。研究结果可以为超高频局部放电信号识别提供参考。The ultra-high frequency partial discharge detection method is one of the most widely used methods for PD monitoring. The PD signal type can be identified by extracting the time-frequency characteristics of UHF PD signals. We proposed a time-frequency feature extraction method for UHF PD signal based on the improved S-transform. Firstly, the S-transform was improved by introducing a new calculation formula for the frequency-domain window width. Then, the six-dimensional statistical features were computed from the frequency-maximum value graphs, which were calculated based on the S-transform modular matrix. Finally, the SVM algorithm was employed to perform the PD signals recognition. The experimental results show that the proposed method can reflect the distribution characteristics of PD components more accurately in the time-frequency domain due to the consideration of both time-domain and frequency-domain resolution. The proposed method can achieve a high classification accuracy of 97.33% even without denoising processing, which proves its strong noise robusticity. Compared with some commonly used feature extraction methods of PD signal, the proposed method can obtain a higher PD type recognition rate. The results provide references for the recognition of UHF PD signals.

关 键 词：局部放电 超高频 改进S变换 支持向量机 特征提取 分类 

分 类 号：TM855[电气工程—高电压与绝缘技术]