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Characterisation of major fault detection features and techniques for the condition-based monitoring of high-speed centrifugal blowers
journal contributionposted on 2016-07-25, 12:37 authored by Samer S.A.A. Gowid, Roger Dixon, Saud Ghani
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.
- Mechanical, Electrical and Manufacturing Engineering
Published inINTERNATIONAL JOURNAL OF ACOUSTICS AND VIBRATION
Pages184 - 191 (8)
CitationGOWID, S., DIXON, R. and GHANI, S., 2016. Characterisation of major fault detection features and techniques for the condition-based monitoring of high-speed centrifugal blowers. International Journal of Acoustics and Vibration, 21(2), pp. 184-191.
Publisher© International Institute of Acoustics and Vibration
- AM (Accepted Manuscript)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThis paper was accepted for publication in the International Journal of Acoustics and Vibration it is reproduced with kind permission of International Institute of Acoustics and Vibration.