eprintid: 2558
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/25/58
datestamp: 2023-11-09 15:50:47
lastmod: 2023-11-09 15:50:47
status_changed: 2023-11-09 15:43:47
type: conference_item
metadata_visibility: show
creators_name: Janier, J.B.
creators_name: Zaim Zaharia, M.F.
creators_name: Karim, S.A.Abd.
title: Use of fuzzy inference system for condition monitoring of induction motor
ispublished: pub
note: cited By 0; Conference of 2nd International Conference on Fundamental and Applied Sciences 2012, ICFAS 2012 ; Conference Date: 12 June 2012 Through 14 June 2012
abstract: Three phase induction motors are commonly used in industry due to its robustness, simplicity of its construction and high reliability. The tasks performed by these motors grow increasingly complex because of modern industries hence there is a need to determine the faults. Early detection of faults will reduce an unscheduled machine downtime that can upset production deadlines and may cause heavy financial losses. This paper is focused in developing a computer based system using Fuzzy Inference system's membership function. An unusual increase in vibration of the motor could be an indicator of faulty condition hence the vibration of the motor of an induction motor was used as an input, whereas the output is the motor condition. An inference system of the Fuzzy Logic was created to classify the vibration characteristics of the motor which is called vibration analysis. The system classified the motor of the gas distribution pump condition as from 'acceptable' to 'monitor closely'. The early detection of unusual increase in vibration of the induction motor is an important part of a predictive maintenance for motor driven machinery. © 2012 American Institute of Physics.
date: 2012
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874157908&doi=10.1063%2f1.4757510&partnerID=40&md5=43d995c0ab18fd1a0f51b55f6e5c099a
id_number: 10.1063/1.4757510
full_text_status: none
publication: AIP Conference Proceedings
volume: 1482
place_of_pub: Kuala Lumpur
pagerange: 441-445
refereed: TRUE
isbn: 9780735410947
issn: 0094243X
citation:   Janier, J.B. and Zaim Zaharia, M.F. and Karim, S.A.Abd.  (2012) Use of fuzzy inference system for condition monitoring of induction motor.  In: UNSPECIFIED.