Rolling Bearing Diagnosing Method Based on Time Domain Analysis and Adaptive Fuzzy C -Means Clustering
Joint Authors
Fu, Sheng
Liu, Kun
Xu, Yonggang
Liu, Yi
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Vibration signal analysis is one of the most effective methods for mechanical fault diagnosis.
Available part of the information is always concealed in component noise, which makes it much more difficult to detect the defection, especially at early stage of the development.
This paper presents a new approach for mechanical fault diagnosis based on time domain analysis and adaptive fuzzy C -means clustering.
By analyzing vibration signal collected, nine common time domain parameters are calculated.
This lot of data constitutes data matrix as characteristic vectors to be detected.
And using adaptive fuzzy C -means clustering, the optimal clustering number can be gotten then to recognize different fault types.
Moreover, five parameters, including variance, RMS, kurtosis, skewness, and crest factor, of the nine are selected as the new eigenvector matrix to be clustered for more optimal clustering performance.
The test results demonstrate that the proposed approach has a sensitive reflection towards fault identifications, including slight fault.
American Psychological Association (APA)
Fu, Sheng& Liu, Kun& Xu, Yonggang& Liu, Yi. 2015. Rolling Bearing Diagnosing Method Based on Time Domain Analysis and Adaptive Fuzzy C -Means Clustering. Shock and Vibration،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1120087
Modern Language Association (MLA)
Fu, Sheng…[et al.]. Rolling Bearing Diagnosing Method Based on Time Domain Analysis and Adaptive Fuzzy C -Means Clustering. Shock and Vibration No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1120087
American Medical Association (AMA)
Fu, Sheng& Liu, Kun& Xu, Yonggang& Liu, Yi. Rolling Bearing Diagnosing Method Based on Time Domain Analysis and Adaptive Fuzzy C -Means Clustering. Shock and Vibration. 2015. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1120087
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1120087