Multiple Faults Diagnosis of Induction Motor Using Artificial Neural Network

被引：9

作者：

Jigyasu, Rajvardhan ^{[1
]}

Mathew, Lini ^{[1
]}

Sharma, Amandeep ^{[1
]}

机构：

[1] Natl Inst Tech Teachers Training & Res, Elect Engn Dept, Sect 26, Chandigarh 160019, India

来源：

ADVANCED INFORMATICS FOR COMPUTING RESEARCH, ICAICR 2018, PT I | 2019年 / 955卷

关键词：

Induction motor; Fault detection; Fault diagnosis; Artificial intelligence; ANN; Transfer functions; Time domain analysis;

D O I：

10.1007/978-981-13-3140-4_63

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents multiple fault diagnosis and detection using artificial neural feed forward network. In this work analysis is done on induction motor, as these motor are widely used in industries because of their robustness, easy maintenance etc. The current and vibration responses of healthy motor, motor with bearing, rotor and stator defects are analysed. The feature extraction process is done in time domain only. From the results it is cleared that among various transfer functions in ANN the trainlm performs best and traingdm performs worst for fault detection.

引用

页码：701 / 710

页数：10

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