Determination of transformer health condition using artificial neural networks
Determination of transformer health condition using artificial neural networks
复制标题
使用人工神经网络确定变压器健康状况
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
M. Ibrahim
中科院分区：
文献类型：
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作者：
A. Abu;Magdy M. A. Salama;M. Ibrahim
本文提出了一种基于诊断测试来评估Transformer健康状况的方法。采用前馈人工神经网络（FFANN）对Transformer的健康指标进行辨识。健康指数用于发现Transformer的健康状况。FFANN的训练是使用59个工作变压器的真实的测量值完成的。用29台工作变压器的真实的数据对训练好的神经网络性能进行了测试。训练后的FFANN的性能评估表明，训练后的神经网络是可靠的，在寻找任何工作的Transformer的健康状况。
This paper presents a method to estimate a transformer health condition based on diagnostic tests. A feed forward artificial neural network (FFANN) is used to find the health index of the transformer. The health index is used to find the health condition of the transformer. The training of the FFANN is done using real measurements of 59 working transformers. The testing of the trained neural network performance is done using real data for 29 working transformers. The performance evaluation of the trained FFANN shows that the trained neural network is reliable in finding the health condition of any working transformer.