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http://dx.doi.org/10.7471/ikeee.2020.24.3.883

Diagnosis Method for Stator-Faults in Induction Motor using Park's Vector Pattern and Convolution Neural Network  

Goh, Yeong-Jin (Dept. of Electrical Engineering, Tongmyong University)
Kim, Gwi-Nam (Dept. of Mechanical and Automotive Engineering, Suncheon Jeil College)
Kim, YongHyeon (Dept. of Electrical and Semiconductor Engineering, Chonnam National University)
Lee, Buhm (Dept. of Electrical and Semiconductor Engineering, Chonnam National University)
Kim, Kyoung-Min (Dept. of Electrical and Semiconductor Engineering, Chonnam National University)
Publication Information
Journal of IKEEE / v.24, no.3, 2020 , pp. 883-889 More about this Journal
Abstract
In this paper, we propose a method to use PV(Park's Vector) pattern for inductive motor stator fault diagnosis using CNN(Convolution Neural Network). The conventional CNN based fault diagnosis method was performed by imaging three-phase currents, but this method was troublesome to perform normalization by artificially setting the starting point and phase of current. However, when using PV pattern, the problem of normalization could be solved because the 3-phase current shows a certain circular pattern. In addition, the proposed method is proved to be superior in the accuracy of CNN by 18.18[%] compared to the previous current data image due to the autonomic normalization.
Keywords
3-Phase Induction Motor; Fault Diagnosis; ITSC; CNN; PVA;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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