Publication Type:

Journal Article

Source:

International Journal of Control and Automation, Volume 3, Number 2, p.9-20 (2010)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-79961196341&partnerID=40&md5=dc720c918d53fe1402ee49684dd49226

Keywords:

Accelerometers, Bearing fault, Bearings (machine parts), Electrical faults, Hall-effect sensors, Induction motors, Mechanical faults, Motor current signature analysis, Multi-class classification, Multi-scale Decomposition, Neural networks, Signal processing, Support vector machines, Vibrations (mechanical), Wavelet packet transforms

Abstract:

In this paper a novel approach to detect various faults occurring in the induction motor is presented. Both vibration and motor current signature analysis are performed to detect the mechanical and electrical faults. Multi-scale decomposition process using wavelet packet transform is performed on the obtained signal to extract the features. The extracted features are given to a classifier to identify whether a fault has occurred. If a fault exists, it identifies the fault location and isolates it. The various faults discussed in this paper are: mechanical faults- such as bearing faults and electrical faults occurring in the rotor and stator parts of an induction motor. Multiple Support Vector Machine using the one-against-others approach is used to obtain multi-class classification of fault.

Notes:

cited By (since 1996)11

Cite this Research Publication

K. B. Aravindh, Saranya, G., Selvakumar, R., R. Shree, S., Saranya, M., and Sumesh, E. P., “Fault detection in Induction motor using WPT and Multiple SVM”, International Journal of Control and Automation, vol. 3, pp. 9-20, 2010.