现代电子技术2017，Vol.40Issue(14)：174-177,182,5.DOI:10.16652/j.issn.1004-373x.2017.14.047
一种新的电能质量扰动特征提取与识别方法
A new features extraction and recognition method for power quality disturbance signals
摘要
Abstract
To overcome the shortcomings of low recognition accuracy caused by improper feature selection and extraction in power quality disturbance recognition,a new feature extraction and recognition method is proposed based on the sample points of power quality disturbance amplitude of mathematical statistics and PSO-SVM.According to the amplitude distribution difference over 10 cycles of signals,the number of samples in amplitude range of each section is calculated,and then used as features of different disturbances after preprocessing.PSO-SVM classifier is used for classification recognition of multiple disturbance signals.The proposed method is simple in the process of feature extraction and efficient in computation.The simulation results show that the proposed method is capable of classifying various disturbance signals at a high speed,and has a higher recognition accuracy and better anti-noise performance in comparison with the traditional methods.关键词
电能质量/数学统计/特征提取/PSO-SVMKey words
power quality/mathematical statistics/features extraction/PSO-SVM分类
信息技术与安全科学引用本文复制引用
熊建平,陈克绪,马鲁娟,肖露欣,吴建华..一种新的电能质量扰动特征提取与识别方法[J].现代电子技术,2017,40(14):174-177,182,5.基金项目
国家自然科学基金项目(61662047) （61662047）
