SciELO journals
Browse
1/1
15 files

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

dataset
posted on 2018-09-19, 03:05 authored by L.I. SANTOS, R.M. PALHARES, M.F.S.V. D’ANGELO, J.B. MENDES, R.R. VELOSO, P.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.

History

Usage metrics

    TEMA (São Carlos)

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC