Artificial neural network based fault identification scheme implementation for a three-phase induction motor

被引：34

作者：

Kolla, Sri R. ^{[1
]}

Altman, Shawn D. ^{[1
]}

机构：

[1] Bowling Green State Univ, Dept Technol Syst, Elect & Comp Technol Program, Bowling Green, OH 43403 USA

来源：

ISA TRANSACTIONS | 2007年 / 46卷 / 02期

关键词：

artificial intelligence; neural networks; induction motor; faults; protection; relays;

D O I：

10.1016/j.isatra.2006.08.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents results from the implementation and testing of a PC based monitoring and fault identification scheme for a three-phase induction motor using artificial neural networks (ANNs). To accomplish the task, a hardware system is designed and built to acquire three-phase voltages and currents from a 1/3 HP squirrel-cage, three-phase induction motor. A software program is written to read the voltages and currents, which are first used to train a feed-forward neural network structure using the JavaNNS program. The trained network is placed in a LabVIEW (TM) based program formula node that monitors the voltages and currents online and displays the fault conditions and turns the motor off. The complete system is successfully tested in real time by creating different faults on the motor. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

引用

页码：261 / 266

页数：6

共 16 条

[1]

*ABB REL DIV, 1994, PROT REL THEOR APPL

[2]

ALTMAN SD, 2004, REAL TIME IMPLEMENTA

[3]

Caudill M., 1992, Understanding Neural Networks: Basic networks

[4]

Chow M., 1991, J NEURAL NETWORK COM, V2, P26