An intelligent machinery fault diagnosis method based on wavelet packet analysis and support vector machine
In this paper,a new intelligent method for the fault diagnosis of the roller bearing is proposed based on wavelet packet analysis (WPA) and support machine (SVM).In fault diagnosis for mechanical systems,information about stability and mutability can be further acquired through WPA from original signal.The faulty vibration signals obtained from rotating machinery are decomposed by WPA via Dmeyer wavelet.An effective fault diagnosis algorithm based on SVM approach is proposed and applied to roller bearing.The extracted features are applied to SVM for estimating fault type.Compared to conventional back-propagation network (BPN),the superiority of the SVM method is shown in the success of fault diagnosis.The test results of SVM demonstrate that the applying of energy criterion to vibration signals after WPA is a very powerful and reliable method and hence estimating fault type on roller bearing accurately and quickly.
Wavelet packet analysis support vector machine fault diagnosis
Xian Guangming Zeng Biqing
Computer Engineering Department of Nanhai.Campus, South China Normal University, Foshan,Guangdong 528225, China
国内会议
山东泰安
英文
550-553
2009-08-15（万方平台首次上网日期，不代表论文的发表时间）