Neural Network Approach for Inter-turn Short-Circuit Detection in Induction Motor Stator Winding

被引：4

作者：

Rajamany, Gayatridevi ^{[1
]}

Srinivasan, Sekar ^{[2
]}

机构：

[1] Asan Mem Coll Engn & Technol, Dept EEE, Chennai, Tamil Nadu, India

[2] Hindustan Inst Technol & Sci, Dept EEE, Chennai, Tamil Nadu, India

来源：

ARTIFICIAL INTELLIGENCE AND EVOLUTIONARY COMPUTATIONS IN ENGINEERING SYSTEMS, ICAIECES 2017 | 2018年 / 668卷

关键词：

Induction motor; Artificial neural network; Modeling Inter-turn short circuit; Fault detection; FAULTS;

D O I：

10.1007/978-981-10-7868-2_52

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work deals with neural network approach for automatic detection of stator winding fault of the induction motor. The problem is faced through modeling of induction motor with short circuit in stator winding. Instantaneous phase voltages, peak values of phase currents, and parameters derived from these data are used to train artificial neural network. The output of the neural network classifies the condition of the stator winding. The proposed architecture performs with the selection of a significant feature set, and accurate fault detection results have been obtained.

引用

页码：537 / 550

页数：14

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