Pattern Recognition for Automatic Machinery Fault Diagnosis-Reference-Cited by-同舟云学术

Pattern Recognition for Automatic Machinery Fault Diagnosis

Published:2004-04-01 Issue:2 Volume:126 Page:307-316
ISSN:1048-9002
Container-title:Journal of Vibration and Acoustics
language:en
Short-container-title:

Author:

Sun Qiao¹,Chen Ping¹,Zhang Dajun¹,Xi Fengfeng²

Affiliation:

1. Dept of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4

2. Dept of Mechanical, Aerospace, and Industrial Eng., Ryerson University, Toronto, Ontario, Canada M5B 2K3

Abstract

We present a generic methodology for machinery fault diagnosis through pattern recognition techniques. The proposed method has the advantage of dealing with complicated signatures, such as those present in the vibration signals of rolling element bearings with and without defects. The signature varies with the location and severity of bearing defects, load and speed of the shaft, and different bearing housing structures. More specifically, the proposed technique contains effective feature extraction, good learning ability, reliable feature fusion, and a simple classification algorithm. Examples with experimental testing data were used to illustrate the idea and effectiveness of the proposed method.

Publisher

ASME International

Subject

General Engineering

Link

http://asmedigitalcollection.asme.org/vibrationacoustics/article-pdf/126/2/307/5668200/307_1.pdf

Reference13 articles.

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2. Li, C. Q., and Pickering, C. J. D., 1992, “Robustness and Sensitivity of Non-Dimensional Amplitude Parameters for Diagnosis of Fatigue Spalling,” Condition Monitoring and Diagnostic Technology, 2(3), pp. 81–84.

3. McFadden, P. D., and Smith, J. D., 1984, “Vibration Monitoring of Rolling Element Bearings by the High Frequency Resonance Technique—A Review,” Tribol. Int., 17(1), pp. 3–10.

4. Sun, Q., and Ying, T., 2002, “Singularity Detection Using Continuous Wavelet Transform for Bearing Fault Diagnosis,” Mech. Syst. Signal Process., 16(6), pp. 1025–1041.

5. Xi, F., Sun, Q., and Krishnappa, G., 2000, “Bearing Diagnostics Based on Pattern Recognition of Statistical Parameters,” J. Vib. Control, 6, pp. 375–392.

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