Fault detection using transient machine signals

被引：80

作者：

Timusk, Markus ^{[2
]}

Lipsett, Mike ^{[3
]}

Mechefske, Chris K. ^{[1
]}

机构：

[1] Queens Univ, Dept Mech & Mat Engn, Kingston, ON, Canada

[2] Laurentian Univ, Sch Engn, Sudbury, ON K7L 3N6, Canada

[3] Univ Alberta, Dept Mech Engn, Calgary, AB, Canada

来源：

MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2008年 / 22卷 / 07期

基金：

加拿大自然科学与工程研究理事会;

关键词：

condition monitoring; vibration signal processing; feature extraction; novelty detection;

D O I：

10.1016/j.ymssp.2008.01.013

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper describes the development and testing of a strategy for vibration-based online detection of faults in a particular class of machinery. This machinery is defined by two basic characteristics that preclude it from the application of standard online condition monitoring systems. The first characteristic is the absence of historical fault data. The second characteristic is that the machine is in a constant state of transient operation. An example of such a machine is the swing machinery of an electromechanical excavator. The monitoring strategy presented here employs an anomaly detection scheme together with various methods of signal processing and feature extraction. Experiments are carried out using a laboratory apparatus to show the how various configurations of the system are able to detect different types of faults. The results indicate that this approach is effective and merits further investigation. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：1724 / 1749

页数：26

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