eprintid: 7166
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/71/66
datestamp: 2023-11-09 16:18:58
lastmod: 2023-11-09 16:18:58
status_changed: 2023-11-09 16:08:39
type: article
metadata_visibility: show
creators_name: Irfan, M.
creators_name: Saad, N.
creators_name: Ibrahim, R.
creators_name: Asirvadam, V.S.
creators_name: Magzoub, M.
title: An Intelligent Fault Diagnosis of Induction Motors in an Arbitrary Noisy Environment
ispublished: pub
keywords: Condition monitoring; Decision making; Failure analysis; Fault tolerant computer systems; Induction motors; Spectrum analysis, Adaptive thresholds; Bearing fault; Fault diagnosis systems; Instantaneous power spectrum; Intelligent fault diagnosis; Loading condition; Noisy environment; Online condition monitoring, Fault detection
note: cited By 14
abstract: In this paper, an intelligent fault diagnosis system based on instantaneous power spectrum analysis is proposed. The instantaneous noise variations and sensor off-sets are considered to be one of the common factors that yield erroneous fault tracking in an online condition monitoring and fault diagnosis system. The developed system has the capability to detect bearing inner race defects at incipient stages with in an arbitrary noise conditions. An adaptive threshold has been designed to deal with line current noise ambiguities for decision-making on the existence of small fault signatures. The performance of the developed system has been analyzed theoretically and experimentally on a custom designed test rig under various loading conditions of the motor. © 2015, Springer Science+Business Media New York.
date: 2016
publisher: Springer New York LLC
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84951858141&doi=10.1007%2fs10921-015-0327-3&partnerID=40&md5=3ae2acc278abc155f3f52d069d1bea46
id_number: 10.1007/s10921-015-0327-3
full_text_status: none
publication: Journal of Nondestructive Evaluation
volume: 35
number: 1
pagerange: 1-13
refereed: TRUE
issn: 01959298
citation:   Irfan, M. and Saad, N. and Ibrahim, R. and Asirvadam, V.S. and Magzoub, M.  (2016) An Intelligent Fault Diagnosis of Induction Motors in an Arbitrary Noisy Environment.  Journal of Nondestructive Evaluation, 35 (1).  pp. 1-13.  ISSN 01959298