人工神经网络转子断条感应电动机故障检测

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI:10.1109/NEUREL.2010.5644051

D. Matic, F. Kulić, V. Climente-Alarcon, R. Puche-Panadero

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引用次数: 16

摘要

研究了人工神经网络在转子断条故障在线检测中的应用。通过监测电机电流谱中某些频率的频谱幅值的异常，可以检测故障。将这些判别特征用于前馈反向传播人工神经网络的训练。训练后的网络能够成功地对异步电动机转子状态进行分类。结果以表格和图表的形式呈现。

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Artificial neural networks broken rotor bars induction motor fault detection

Paper deals with application of online rotor broken bar fault detection via artificial neural networks. Fault can be detected by monitoring abnormalities of the spectrum amplitudes at certain frequencies in the motor current spectrum. These discriminative features are used for training of feed-forward backpropagation artificial neural network. Trained network is capable to successfully classify induction motor rotor condition. Results are presented in tables and figures.

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10th Symposium on Neural Network Applications in Electrical Engineering

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