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Fault diagnosis for electromechanical system via extended analytical redundancy relations

Yu, M., Xiao, C., Jiang, W., Yang, S. and Wang, H.ORCID: 0000-0003-2789-9530 (2018) Fault diagnosis for electromechanical system via extended analytical redundancy relations. IEEE Transactions on Industrial Informatics, 14 (12). pp. 5233-5244.

Link to Published Version: https://doi.org/10.1109/TII.2018.2842255
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Abstract

This paper deals with bond-graph-based fault detection, isolation, and estimation, which is applied to a nonlinear electromechanical system, in the presence of parametric faults and nonparametric faults. The concept of extended analytical redundancy relations (EARRs) is developed where the nonparametric faults of both multiplicative and additive natures can be considered and distinguished. The integration of dependent EARR with independent EARR leads to a more efficient fault isolation where the number of potential faults could be decreased. For the purpose of fault estimation, a new pitch adjustment biogeography-based optimization is developed where the pitch adjustment in harmony search is embedded in a biogeography-based optimization mutation stage to enhance the search ability of the algorithm. The proposed methodologies are validated by simulation and experiment results.

Item Type: Journal Article
Publisher: IEEE
Copyright: © 2018 IEEE
URI: http://researchrepository.murdoch.edu.au/id/eprint/53380
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