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Machine Condition Monitoring Using Signal Classification Techniques

Mechanical Engineering Department, National Central University, Chun-Li 320, Taiwan, ROC

P. Sas

Mechanical Engineering Department, Katholieke Universiteit Leuven, Celestijnenlaan 300B, B-3001 Leuven, Belgium

H. Van Brussel

Mechanical Engineering Department, Katholieke Universiteit Leuven, Celestijnenlaan 300B, B-3001 Leuven, Belgium

Two signal classification approaches, based on Wigner-Ville distribution and extended symmetric Itakura distance, are proposed to post-process the time-frequency representations (TFRs) of vibration signatures, with the final aim to arrive at an automated procedure of machine condition monitoring. Three synthetical signals are used to evaluate and compare the classification performance of these techniques. Some related computation issues, such as characters of different TFRs and weighted window length, are discussed. Experimental case studies, joint fault diagnosis, are realized.

Key Words: Signal analysis • machine condition monitoring • feature detection • vibration of machinery

Journal of Vibration and Control, Vol. 9, No. 10, 1103-1120 (2003)
DOI: 10.1177/107754603030683


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