Induction machine fault detection using clone selection programming

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

28 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)8000-8012
Journal / PublicationExpert Systems with Applications
Volume36
Issue number4
Publication statusPublished - May 2009

Abstract

A clonal selection programming (CSP)-based fault detection system is developed for performing induction machine fault detection and analysis. Four feature vectors are extracted from power spectra of machine vibration signals. The extracted features are inputs of an CSP-based classifier for fault identification and classification. In this paper, the proposed CSP-based machine fault diagnostic system has been intensively tested with unbalanced electrical faults and mechanical faults operating at different rotating speeds. The proposed system is not only able to detect electrical and mechanical faults correctly, but the rules generated is also very simple and compact and is easy for people to understand, This will be proved to be extremely useful for practical industrial applications. © 2008 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Classification, Clone selection principle, Immune system, Induction machine fault detection, Programming