Characterisation of major fault detection features and techniques for the condition-based monitoring of high-speed centrifugal blowers
Author | Gowid, Samer |
Author | Dixon, Roger |
Author | Ghani, Saud |
Available date | 2021-09-01T10:03:29Z |
Publication Date | 2016 |
Publication Name | International Journal of Acoustics and Vibrations |
Resource | Scopus |
Abstract | This paper investigates and characterises the major fault detection signal features and techniques for the diagnostics of rotating element bearings and air leakage faults in high-speed centrifugal blowers. The investigation is based on time domain and frequency domain analysis, as well as on process information, vibration, and acoustic emission fault detection techniques. The results showed that the data analysis method applied in this study is effective, as it yielded a detection accuracy of 100%. A lookup table was compiled to provide an integrated solution for the developer of Condition-Based Monitoring (CBM) applications of centrifugal blowers. The major contribution of this paper is the integration and characterisation of the major fault detection features and techniques. |
Language | en |
Publisher | International Institute of Acoustics and Vibrations |
Subject | Acoustic emission testing Blowers Centrifugation Compressors Condition monitoring Fault detection Feature extraction Frequency domain analysis Table lookup Vibration analysis Centrifugal blower Condition-based monitoring Data analysis methods Detection accuracy Detection features Fault detection techniques Integrated solutions Process information Time domain analysis |
Type | Conference Paper |
Pagination | 184-191 |
Issue Number | 2 |
Volume Number | 21 |
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Mechanical & Industrial Engineering [1339 items ]