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经验模式分解在故障诊断中的应用研究进展
引用本文:罗跃纲,张悦,胡红英,付豪,黄逢超,贾海峰.经验模式分解在故障诊断中的应用研究进展[J].大连民族学院学报,2020,22(1):26-32.
作者姓名:罗跃纲  张悦  胡红英  付豪  黄逢超  贾海峰
作者单位:大连民族大学 a.机电工程学院;b.智能感知与先进控制国家民委重点实验室,辽宁 大连 116605
基金项目: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)。
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。

关 键 词:EMD  特征提取  智能识别  信号处理  

Research Progress of Application of Empirical Mode Decomposition in Fault Diagnosis
LUO Yue-gang,ZHANG Yue,HU Hong-ying,FU Hao,HUANG Feng-chao,JIA Hai-feng.Research Progress of Application of Empirical Mode Decomposition in Fault Diagnosis[J].Journal of Dalian Nationalities University,2020,22(1):26-32.
Authors:LUO Yue-gang  ZHANG Yue  HU Hong-ying  FU Hao  HUANG Feng-chao  JIA Hai-feng
Institution:a. School of Electromechanical Engineering; b. Key Laboratory of Intelligent Perception and Advanced Control of State Ethnic Affairs Commission, Dalian Minzu University, Dalian Liaoning 116605, China
Abstract: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.
Keywords:EMD  feature extraction  intelligent recognition  signal processing  
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