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|Title: ||Characterisation of major fault detection features and techniques for the condition-based monitoring of high-speed centrifugal blowers|
|Authors: ||Gowid, Samer|
|Issue Date: ||2016|
|Publisher: ||© International Institute of Acoustics and Vibration|
|Citation: ||GOWID, 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.|
|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.|
|Description: ||This 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.|
|Version: ||Accepted for publication|
|Publisher Link: ||http://dx.doi.org/10.20855/ijav.2016.21.2410|
|Appears in Collections:||Published Articles (Mechanical, Electrical and Manufacturing Engineering)|
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