Shi, Zhanqun, Higson, Andrew, Zheng, Lin, Gu, Fengshou and Ball, Andrew (2006) Automatic Fault Detection Using a Model-Based Approach in the Frequency Domain. In: ASME 8th Biennial Conference on Engineering Systems Design and Analysis, 4-7 July 2006, Torino, Italy. (Unpublished)Metadata only available from this repository.
In this paper, the model-based approach is introduced into rotation machinery fault detection to achieve an automatic feature extraction. The paper starts with a brief review of the model-based approach, including model development, residual generation and fault detection and diagnosis. The applicability of this approach to rotation machinery is then considered. In order to overcome difficulties arising from phase shift and random measurements, the statistical performance of the vibration of rotation machinery is analysed in both time and frequency domains. A consistence model is developed using stochastic process theory. After model validation, the model-based approach is implemented in AC motor fault detection. The residual is generated by comparing the new measurement and the model prediction, by both subtraction and division. Fault detection results prove that the model-based approach is applicable to fault feature extraction for rotation machinery in the frequency domain.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||T Technology > TA Engineering (General). Civil engineering (General)|
|Schools:||Research and Enterprise Directorate
School of Computing and Engineering
|Depositing User:||Elizabeth Boulton|
|Date Deposited:||25 Mar 2015 11:13|
|Last Modified:||25 Mar 2015 11:13|
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