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Fault diagnosis for electromechanical system via extended analytical redundancy relations
Journal article   Peer reviewed

Fault diagnosis for electromechanical system via extended analytical redundancy relations

M. Yu, C. Xiao, W. Jiang, S. Yang and H. Wang
IEEE Transactions on Industrial Informatics, Vol.14(12), pp.5233-5244
2018
DOI: 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.

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29 Times Cited - Web of Science

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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.29 Automation & Control Systems
4.29.923 Industrial Fault Detection
Web Of Science research areas
Automation & Control Systems
Computer Science, Interdisciplinary Applications
Engineering, Industrial
ESI research areas
Engineering
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