Condition Monitoring of Induction Motor using Artificial Neural Network

被引：0
|
作者：
Bhavsar, Ravi C. [1 ]
Patel, Rakeshkumar A. [1 ]
Bhalja, B. R. [2 ]
机构：
[1] Ganpat Univ, UVPCE, Dept Elect Engn, Kherva, India
[2] PDPU, Sch Technol, Dept Elect Engn, Gandhinagar, India
来源：
2014 ANNUAL INTERNATIONAL CONFERENCE ON EMERGING RESEARCH AREAS: MAGNETICS, MACHINES AND DRIVES (AICERA/ICMMD) | 2014年
关键词：
Condition Monitoring; Induction motor; Analytical model; Artificial Intelligence; Artificial Neural Network;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper deals with stator fault detection of induction motor. Mathematical modeling of induction motor for healthy and stator fault condition are explained. In this paper Artificial Neural Network technique is applied for stator fault detection in induction motor. By collecting the simulation data from the mathematical model developed in MATLAB simulink, ANN is trained. 16 different parameters of induction motor have been taken to train the neural network. ANN gives best performance with 10 neurons in hidden layer. The results clearly show that trained neural network can precisely detect the faults before any major problem occurs.
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页数：6
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