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Monitoring and Detecting Health of a Single Phase Induction Motor Using Data Acquisition Interface (DAI) module with Artificial Neural Network

机译:使用带有人工神经网络的数据采集接口(DAI)模块监视和检测单相感应电动机的运行状况

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This paper deals with the problem of detection of induction motor incipient faults and usefulness of Artificial Neural Network (ANN) in this respect. The research work diagnoses the three major faults such as stator inter-turn faults, bearing faults and misalignment faults using some measurable parameters (motor intake current, speed and body temperature). The experimental data for three measurable parameters were generated in the laboratory on specially connected single phase induction motor. The measurable parameters were obtained by a Data Acquisition Interface (DAI) module and neural network algorithm was achieved by using MATLAB programming language. Experimental results show that it is a very good choice to detect incipient faults in single phase induction motor using an ANN algorithm.
机译:本文探讨了感应电动机早期故障的检测以及人工神经网络(ANN)在这方面的实用性。研究工作使用一些可测量的参数(电动机进气电流,速度和体温)诊断出三个主要故障,例如定子匝间故障,轴承故障和不对中故障。在专门连接的单相感应电动机上,在实验室中生成了三个可测量参数的实验数据。通过数据采集接口(DAI)模块获得了可测量的参数,并使用MATLAB编程语言实现了神经网络算法。实验结果表明,使用ANN算法检测单相感应电动机的早期故障是一个很好的选择。

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