Non-stationary signal analysis and transient machining process condition monitoring

被引：27

作者：

Gu, SX ^{[1
]}

Ni, J ^{[1
]}

Yuan, JX ^{[1
]}

机构：

[1] Univ Michigan, SM Wu Mfg Res Ctr, Dept Mech Engn & Appl Mech, Ann Arbor, MI 48109 USA

来源：

INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE | 2002年 / 42卷 / 01期

关键词：

non-stationary machine condition monitoring and diagnosis; machining process; machine signal analysis;

D O I：

10.1016/S0890-6955(01)00097-9

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Non-stationary machine condition monitoring is very important in modem automated manufacturing processes. In this research, an innovative non-stationary (transient) signal analysis approach has been developed for non-stationary machine condition monitoring. It is based on time-frequency distribution analysis and a singular value decomposition approach. The singular value decomposition method is used to extract features from the time-frequency distribution data. These features will serve as machine condition indices and can be easily incorporated for on-line machine condition monitoring and diagnosis. Satisfactory results have been obtained through simulation and experimental data. Experimental studies have demonstrated the effectiveness of the proposed method for transient machine and process condition monitoring. (C) 2001 Elsevier Science Ltd. All rights reserved.

引用

页码：41 / 51

页数：11