文档介绍：ARTICLE IN PRESS
JOURNAL OF
SOUND AND
VIBRATION
Journal of Sound and Vibration 287 (2005) 25–43
ate/jsvi
Cavitation detection of butterfly valve using
support vector machines
Bo-Suk Yanga,Ã, Won-Woo Hwanga, Myung-Han Kob, Soo-JongLee a
aIntelligent Mechanics Laboratory, School of Mechanical Engineering, Pukyong National University, San 100,
Yongdang-dong, Nam-gu, Busan 608-739, South Korea
bPaldang Regional Office, Korea Water Resources Corporation, San 13, Bealmi-dong, Hanam,
Kyonggi 465-130, South Korea
Received 23 June 2003; received in revised form 27 April 2004; accepted 25 October 2004
Available online 23 December 2004
Abstract
Butterfly valves are popularly used in service in the industrial and water works pipeline systems with large
diameter because of its lightweight, simple structure and the rapidity of its manipulation. Sometimes
cavitation can occur, resultingin noise, vibration and rapid deterioration of the valve trim, and do not
allow further operation. Thus, monitoringof cavitation is of economic interest and is very important in
industry.
This paper proposes a condition monitoringscheme usingstatistical feature evaluation and support
vector machine (SVM) to detect the cavitation conditions of butterfly valve which used as a flow control
valve at the pumpingstations. The stationary features of vibration signalsare extracted from statistical
moments. The SVMs are trained, and then classify normal and cavitation conditions of control valves. The
SVMs with the anized feature vectors can distinguish the class of the untrained and untested data. The
classification validity of this method is examined by various signals acquired from butterfly valves in the
pumpingstations. And the classification ess rate pared with that of anizingfeature map
work (SOFM).
r 2004 Elsevier Ltd. All rights reserved.
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E-mail address: ******@ (B.-S. Yang).
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