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首页> 外文期刊>International Journal of Engineering Research and Applications >Detection of Static Air-Gap Eccentricity in Three Phase induction Motor by Using Artificial Neural Network (ANN)
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Detection of Static Air-Gap Eccentricity in Three Phase induction Motor by Using Artificial Neural Network (ANN)

机译：基于人工神经网络的三相感应电动机静态气隙偏心检测

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This paper presents the effect of the static air-gap eccentricity on the performance of a three phase induction motor .The Artificial Neural Network (ANN) approach has been used to detect this fault .This technique depends upon the amplitude of the positive and negative harmonics of the frequency. Two motors of (2.2 Kw) have been used to achieve the actual fault and desirable data at no-load, half-load and full-load conditions. Motor Current Signature analysis (MCSA) based on stator current has been used to detect eccentricity fault. Feed forward neural network and error back propagation training algorithms are used to perform the motor fault detection.........
机译：本文介绍了静态气隙偏心率对三相感应电动机性能的影响。已使用人工神经网络（ANN）方法检测此故障。此技术取决于正负谐波的幅度的频率。在空载，半载和满载条件下，已经使用两台（2.2 Kw）的电动机来实现实际故障和所需的数据。基于定子电流的电动机电流签名分析（MCSA）已用于检测偏心故障。前馈神经网络和误差反向传播训练算法用于执行电机故障检测.........

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