电气传动2024，Vol.54Issue(5)：26-33,72,9.DOI:10.19457/j.1001-2095.dqcd24703
经验小波变换和改进S变换结合的电能质量检测与识别方法
Power Quality Detection and Recognition Method Based on Empirical Wavelet Transform and Improved S-transform
摘要
Abstract
In order to analyze the power quality problem of actual power network under the influence of uncertain interference factors,a power quality detection and recognition method combining empirical wavelet transform(EWT)and improved S-transform was proposed.On the one hand,the frequency,amplitude and time parameters of the AM-FM component were accurately extracted by using the EWT joint normalization direct orthogonal(NDQ)algorithm and singular value decomposition(SVD)algorithm.On the other hand,considering the instantaneous amplitude fluctuation of the EWT algorithm in the high noise environment,the improved S-transform was introduced to extract the time-frequency information of power quality disturbances under the high noise interference.Finally,based on the disturbance feature vectors extracted by EWT and improved S transform,the power quality disturbance recognition classifier optimized by the support vector machine(SVM)based on improved particle swarm optimization(IPSO)algorithm was used to accurately identify the disturbance types.Simulation and experiments show that the average recognition accuracy of the proposed method is 93.23%in the case of composite disturbance recognition and classification,and it can accurately identify four kinds of measured disturbance signals.关键词
电能质量/扰动检测识别/经验小波变换/快速多分辨率S变换/改进粒子群优化/支持向量机Key words
power quality/disturbance detection and identification/empirical wavelet transform(EWT)/fast multi-resolution S-transform(FMST)/improved particle swarm optimization(IPSO)/support vector machines(SVM)分类
信息技术与安全科学引用本文复制引用
李宁,王茹月,朱龙辉..经验小波变换和改进S变换结合的电能质量检测与识别方法[J].电气传动,2024,54(5):26-33,72,9.基金项目
国家自然科学基金(52177193) （52177193）
陕西省重点研发计划(2022GY-182) （2022GY-182）
国家留学基金委国际清洁能源拔尖人才项目([2018]5046,[2019]157) （[2018]5046,[2019]157）
西安市科技计划项目(22GXFW0078) （22GXFW0078）
