用神经网络识别交联聚乙烯电缆线路局部放电噪声

G. Katsuta, H. Suzuki, H. Eshima, T. Endoh
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引用次数: 5

摘要

利用神经网络系统对交联聚乙烯(XLPE)电力电缆中局部放电信号与外界噪声的区分进行了实验研究。用PD脉冲记录仪测量了带有人工缺陷的66kv交联聚乙烯电缆的PD信号和外部噪声。该神经网络是一个具有前馈连接的三层人工神经系统,其学习方法为反向传播算法。它的输入信息是放电幅度、脉冲计数数和外加电压相角的组合。
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Discrimination of partial discharge from noise in XLPE cable lines using a neural network
This paper describes an experimental study of the discrimination of partial discharge (PD) signals from external noise in a cross-linked polyethylene (XLPE) power cable by using a neural network (NN) system. Measurement of PD signal and external noise was carried out with a PD pulse recorder for a 66 kV XLPE cable with an artificial defect and a drill. The NN was a three-layer artificial neural system with feedforward connections, and its learning method was a backpropagation algorithm. Its input information was a combination of the discharge magnitude, the number of pulse counts, and the phase angle of applied voltage.<>
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