电力系统保护与控制2011，Vol.39Issue(14)：143-147,5.
基于分形特征的最小二乘支持向量机局部放电模式识别
The pattern recognition of partial discharge based on fractal characteristics using LS-SVM
任先文 1薛雷 1宋阳 1郭丹丹 1沈重1
作者信息
摘要
Abstract
In order to improve the correct rate of partial discharge (PD) pattern recognition, a method based on the least squares support vector machine ( LS-SVM ) is put forward to recognize the discharge models.Using the wavelet analysis technology and the fractal theory, the fractal dimension of signals in each frequency-band can be calculated, and the reciprocal of fractal dimensions of each frequency-band are input to multi-classified LS-SVMs for training to implement PD samples classification.The results show that by adopting fractal characteristics, the PD signal information is concentrated and the time-consuming problem in parameter determination is solved.Moreover, the method enables to detect a high recognition rate under condition of small samples, and has good value in PD pattern recognition.关键词
局部放电/最小二乘支持向量机/小波包分析/分形维数/模式识别Key words
partial discharge/ least squares-support vector machine/ wavelet packet analysis/ fractal dimension/ pattern recognition分类
信息技术与安全科学引用本文复制引用
任先文,薛雷,宋阳,郭丹丹,沈重..基于分形特征的最小二乘支持向量机局部放电模式识别[J].电力系统保护与控制,2011,39(14):143-147,5.
