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Fault diagnosis of rotating machinery based on empirical mode decomposition

科研成果: 书/报告/会议事项章节章节同行评审

22 引用 (Scopus)

摘要

Rotating machinery covers a broad range of mechanical equipment in industrial applications. It generally operates under tough working environment and is therefore subject to faults easily. Vibration signals collected in the working process have valuable contributions for the presentation of conditions of the rotating machinery. Consequently, using signal processing techniques, these faults could be detected and diagnosed. Empirical mode decomposition (EMD) is one of the most powerful signal processing techniques and has been widely applied in fault diagnosis of rotating machinery. This chapter attempts to introduce the recent research and development of EMD in fault diagnosis of rotating machinery, including basic concepts and fundamental theories about EMD methods and improved EMD methods. Moreover, the applications of EMD methods and improved EMD methods in fault diagnosis of common and key components of rotating machinery, like rotors, gears and rolling element bearings, are described in details.

源语言英语
主期刊名Smart Sensors, Measurement and Instrumentation
出版商Springer International Publishing
259-292
页数34
DOI
出版状态已出版 - 2017

出版系列

姓名Smart Sensors, Measurement and Instrumentation
26
ISSN(印刷版)2194-8402
ISSN(电子版)2194-8410

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