NDLI: Weibull distribution parameters for fault feature extraction of rolling bearing

Content Provider	IEEE Xplore Digital Library
Author	Peng Tao Jiang Haiyan Xie Yong
Copyright Year	2011
Description	Author affiliation: School of Information Science and Engineering, Changsha, 410083 China (Peng Tao) \|\| College of Electrical Engineering, Hunan, University of Technology, Zhuzhou, 412008 China (Jiang Haiyan; Xie Yong)
Abstract	A novel approach to fault feature extraction using Weibull distribution parameters is proposed. After the original signal of bearing vibration is modeled as the Weibull distribution, its scale parameter is extracted as a new feature vector for the bearing running state. The tests results of fault diagnosis of the rolling bearing verify that this new feature can catch the regularity of changes in the information of bearing vibration more sensitively and accurately, and have higher separability suitable for pattern recognition by support vector machine classifier.
Starting Page	69
Ending Page	74
File Size	795500
Page Count	6
File Format	PDF
ISBN	9781424487370
e-ISBN	9781424487387
DOI	10.1109/CCDC.2011.5968148
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vibrations Support vector machines Shape Weibull Distribution Rolling Bearing Fault Diagnosis Feature Extraction Feature extraction Wavelength division multiplexing Scale Parameter Weibull distribution Frequency domain analysis
Content Type	Text
Resource Type	Article

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