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Faults Diagnosis of Induction Motors by Neural Network  

김부열 (순천대학교 정보통신공학부)
우혁재 (순천대학교 정보통신공학부)
송명현 (순천대학교 정보통신공학부)
박중조 (경상대학교 전기전자공학부)
김경민 (여수대학교 전자통신 및 전기공학부)
정회범 (순천대학교 기계자동차공학부)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.6, no.2, 2002 , pp. 294-299 More about this Journal
Abstract
This paper presents a faults diagnosis technique of induction motors based on a neural network. Only stator current is measured, transformed by using FFT and normalized for the training. Healthy, bearing fault, stator fault and rotor end-ring fault motors are prepared to obtain the learning data and diagnose the several faults. For more effective diagnosis, the load rate is changed by 100%, 60%, 30% of full load and the obtained are applied to the teaming process. The experimental results show the proposed method is very detectable and applicable to the real diagnosis system.
Keywords
Faults Diagnosis; Neural Network; Induction Motor; FFT;
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