A New Scheme for Fault Detection and Classification Applied to DC Motor

Author:

Santos Laércio I.,Palhares Reinaldo M.,D'Angelo Marcos F. S. V.,Mendes João B.,Veloso Renê R.,Ekel Petr Y.

Abstract

This study presents an approach for fault detection and classification in a DC drive system. The fault is detected by a classical Luenberger observer. After the fault detection, the fault classification is started. The fault classification, the main contribution of this paper, is based on a representation which combines the Subctrative Clustering algorithm with an adaptation of Particle Swarm Clustering.

Publisher

Brazilian Society for Computational and Applied Mathematics (SBMAC)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fault Detection of a Networked Control System and Its Application to a DC Motor;International Journal of Control, Automation and Systems;2023-04-19

2. Chemical static equipment commonly used sensor fault detection and isolation methods;Journal of Intelligent & Fuzzy Systems;2021-05-22

3. Swarm intelligence and fuzzy sets for bed exit detection of elderly;Journal of Intelligent & Fuzzy Systems;2020-07-17

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