机械科学与技术2018，Vol.37Issue(7)：1013-1021,9.DOI:10.13433/j.cnki.1003-8728.2018.0703
最近相似距离延拓法耦合平行延拓法抑制EMD端点效应
Restraining Boundary Effect of EMD based on Nearest Similarity Distance Continuation and Parallel Extending Methods
摘要
Abstract
In this paper,the research considers the inner regularity of the signal,which improves the method of boundary extending based on the method of the nearest similarity distance continuation and parallel extending method.The regularity strength of signal is determined by calculatins the similarity distance between the boundary wave and any internal signal wave.When the inherent regularity is strong,the nearest similarity distance continuation method is conducted to maintain the inherent tendency to the greatest extent;while the signal is week regularity and the signal edge changes abnormally,the local information at the edges is considered only to conduct the parallel extending method.In order to prove the improved algorithm,this paper calculates the matching distance,waveform similarity coefficient and error in marginal spectrum of frequency through the simulation analysis and tests of fault diagnosis of rolling bearings of IMFs and sirulation signal component.The results demonstrate that matching distances are 33787,7.2404,7.390 7,waveform similarity coefficients are 0999 9,0.9977,0903 4 anderror in marginal spectrum in 5 Hz is 62％ by the improved algorithm.Containers among directly continuation,parallel extending method,this method can suppress end effect of EMD.This method can improve the decomposition accuracy and achieve availably fault feature extraction,which can provide the reference for fault diagnosis of machine.关键词
经验模态分解/端点效应/最近相似距离延拓法/平行延拓法Key words
EMD/boundary effect/nearest similarity distance continuation method/parallel extending method分类
能源科技引用本文复制引用
何振鹏,朱志琪,谢海超,王雅文,李宗强,何锐,杜超平,李金兰..最近相似距离延拓法耦合平行延拓法抑制EMD端点效应[J].机械科学与技术,2018,37(7):1013-1021,9.基金项目
国家自然科学基金项目(51505482)、中国民航局科技计划项目(MHRD20160106)、中央高校基本科研业务费专项资金项目(3122015C015)、中国民航大学科研启动基金项目(2014QD02S)及福建省清洁燃烧与能源高效利用工程技术研究中心开放课题(KF201703)资助 （51505482）
