@inproceedings{scholars2558, year = {2012}, pages = {441--445}, journal = {AIP Conference Proceedings}, doi = {10.1063/1.4757510}, 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}, volume = {1482}, address = {Kuala Lumpur}, title = {Use of fuzzy inference system for condition monitoring of induction motor}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84874157908&doi=10.1063\%2f1.4757510&partnerID=40&md5=43d995c0ab18fd1a0f51b55f6e5c099a}, 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. {\^A}{\copyright} 2012 American Institute of Physics.}, author = {Janier, J. B. and Zaim Zaharia, M. F. and Karim, S. A. Abd.}, issn = {0094243X}, isbn = {9780735410947} }