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A Time Series Analysis and Neural Network Based Scheme for Fault Diagnosis of Transformers

机译:变压器故障诊断的时间序列分析与神经网络

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This research presents a time series analysis and artificial neural network (ANN)-based scheme for fault diagnosis of power transformers, which extracts the characteristic parameters of the faults of the transformer from the results of time series analysis and bases on this basis establishes the corresponding back propagation (BP) neural network to detect the transformer operating faults. The simulation experimental results show that as compared to the related works, the proposed approach effectively integrates the superiority of time series analysis and BP neural network and thus can greatly improve the diagnosis accuracy and reliability.
机译:本研究提出了一种时间序列分析和人工神经网络(ANN)的电力变压器故障诊断方案,从而从时间序列分析结果和基础上提取了变压器故障的特性参数,在此基础上建立了相应的后传播(BP)神经网络检测变压器操作故障。仿真实验结果表明,与相关工程相比,所提出的方法有效地集成了时间序列分析和BP神经网络的优越性,从而大大提高了诊断精度和可靠性。

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