The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 32-377
Full Name: Peng Chen
Position: Professor
Age: ON
Sex: Male
Address: 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507
Country: JAPAN
Tel: +81-59-231-9592
Tel prefix:
Fax: +81-59-231-9592
E-mail address: chen@bio.mie-u.ac.jp
Other E-mails: wanghq_buct@hotmail.com
Title of the Paper: Fault Diagnosis Method Based on Kurtosis Wave and Information Divergence for Rolling Element Bearings
Authors as they appear in the Paper: Huaqing Wang, Peng Chen
Email addresses of all the authors: chen@bio.mie-u.ac.jp,wanghq_buct@hotmail.com
Number of paper pages: 10
Abstract: Fault diagnosis depends largely on the feature analysis of vibration signals. However, feature extraction for fault diagnosis is difficult because the vibration signals often contain a strong noise component. Noises stronger than the actual fault signal may interfere with diagnosis and, ultimately, cause misdiagnosis. In order to extract the feature from the fault signal highly contaminated by the noise, and accurately identify the fault types, a novel diagnosis method is proposed based on the kurtosis wave and information divergence for fault detection of a rolling element bearing. A kurtosis wave (KW) is defined in the time domain using the vibration signal, and a method to obtain the kurtosis information wave (KIW) is also proposed based on Kullback-Leibler (KL) divergence using the kurtosis wave. Practical example of diagnosis for the outer-race defect of a bearing is provided to verify the effectiveness of the proposed method. This paper also compares the prop!
osed method with the two envelope analysis techniques, namely the wavelet transform- and the FFT-based envelope analysis techniques. The analyzed results show that the feature of a bearing defect is extracted clearly, and the bearing fault can be effectively identified by the proposed method. However, the fault cannot be detected using either of the compared techniques.
Keywords: Fault Diagnosis, Rolling Element Bearing, Envelope Analysis, Kurtosis Wave, Information Divergence
EXTENSION of the file: .doc
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress:
IP ADDRESS: 133.67.106.190
