摘要
随着人们对机械振动领域研究的深入,经验模式分解(EMD)被越来越多的应用于机械故障特征提取与智能识别中。针对近年来国内外学者使用EMD的研究成果及发展趋势进行综述,主要包含经验模式分解的基本原理,经验模式分解在故障特征提取、智能识别方面的应用以及最新进展。同时对EMD在机械故障特征提取及故障识别中的应用进行了系统的归纳,为实际工况中机械故障诊断提供了理论依据,提出了使用EMD进行机械故障特征提取待解决的相关问题,并对未来发展趋势进行了展望。
With the deepening research in the field of mechanical vibration,empirical mode decomposition(EMD)is more and more used in the extraction and intelligent recognition of mechanical fault features.This article reviews the research results and development trends of domestic and foreign scholars using EMD in recent years.It mainly includes the basic principles of empirical mode decomposition,and the application of it in fault feature extraction,intelligent recognition and the latest progress.This article also systematically summarizes the application of EMD in mechanical fault feature extraction and fault identification,which provides a theoretical basis for mechanical fault diagnosis in actual working conditions,proposes related problems to be solved when using EMD to diagnose mechanical faults and prospects for future development trends.
作者
罗跃纲
张悦
胡红英
付豪
黄逢超
贾海峰
LUO Yue-gang;ZHANG Yue;HU Hong-ying;FU Hao;HUANG Feng-chao;JIA Hai-feng(School of Electromechanical Engineering,Dalian Minzu University,Dalian Liaoning 116605,China;Key Laboratory of Intelligent Perception and Advanced Control of State Ethnic Affairs Commission,Dalian Minzu University,Dalian Liaoning 116605,China)
出处
《大连民族大学学报》
2020年第1期26-32,共7页
Journal of Dalian Minzu University
基金
国家自然科学基金资助项目(51875085)
辽宁省自然科学基金资助项目(20170540205)
关键词
EMD
特征提取
智能识别
信号处理
EMD
feature extraction
intelligent recognition
signal processing
