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

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

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.

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DOI: https://doi.org/10.5540/tema.2018.019.02.327

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TEMA - Trends in Applied and Computational Mathematics

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