电力系统及其自动化学报2019，Vol.31Issue(5)：1-7,7.DOI:10.19635/j.cnki.csu-epsa.000038
电能质量扰动识别的小波压缩感知方法
Power Quality Disturbance Recognition Method Based on Wavelet Compressive Sensing
摘要
Abstract
To overcome the disadvantages in the power quality signal disturbance recognition based on wavelet trans?form,such as a large amount of data and a low accuracy rate,a novel power quality disturbance recognition method based on wavelet compressive sensing is proposed. First,the sparsity of disturbance signal in wavelet domain is deter?mined. Second,wavelet compressive sensing is used to reduce dimensions,and a few measurement data can be ob?tained. Then,the sparsity coefficient in every layer can be obtained by orthogonal matching pursuit(OMP)algorithm to form a sparsity matrix. Finally,eigenvectors are formed by the extracted maximum,standard deviation,kurtosis,etc., and they are further input into the neural network system for training so as to classify and identify the types of distur?bance signal. This method is featured by less sampling data,easy process,and simple extraction of characteristics,etc. Simulation results demonstrate that the recognition rates obtained using the proposed method for seven typical single and mixed disturbance signals reach 99.50% and 99.43% respectively in an ideal environment,and above 97% and 98% respectively in a noisy environment,showing stronger robustness and better accuracy.关键词
电能质量/压缩感知/扰动识别/小波变换/BP神经网络Key words
power quality/compressive sensing/disturbance recognition/wavelet transform/BP neural network分类
信息技术与安全科学引用本文复制引用
吴志宇,朱云芳,侯怡爽,陈维荣..电能质量扰动识别的小波压缩感知方法[J].电力系统及其自动化学报,2019,31(5):1-7,7.基金项目
国际科技合作专项资助项目(2013DFA11040) （2013DFA11040）
国家自然科学基金资助项目(61571324) （61571324）
