Please use this identifier to cite or link to this item: https://doi.org/10.1109/IEMDC.2001.939423
Title: An on-line neurofuzzy approach for detecting faults in induction motors
Authors: Tan, W.W. 
Huo, H. 
Issue Date: 2001
Source: Tan, W.W.,Huo, H. (2001). An on-line neurofuzzy approach for detecting faults in induction motors. IEMDC 2001 - IEEE International Electric Machines and Drives Conference : 878-883. ScholarBank@NUS Repository. https://doi.org/10.1109/IEMDC.2001.939423
Abstract: A broken rotor bar is one of the most common type of faults that may occur in an induction motor system. This paper is devoted to investigating the possibility of performing online monitoring of the condition of asynchronous machines. The fault detection scheme uses a neurofuzzy model of the static characteristics of the motor to generate residuals. Although the influence of a cracked rotor bar and an increase in the motor loading are similar, simulation results show that the neurofuzzy model-based fault detector is able to detect the presence of a partially broken bar regardless of the loading conditions. © 2001 IEEE.
Source Title: IEMDC 2001 - IEEE International Electric Machines and Drives Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/69354
ISBN: 0780370910
DOI: 10.1109/IEMDC.2001.939423
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