证据理论在变压器故障诊断中的应用

为了提高变压器故障诊断的准确性，引入了一种基于证据理论的诊断方法。根据变压器故障的特征数据，采用2个并行的BP神经网络对变压器进行局部故障诊断，以获得彼此独立的证据，再采用证据理论对各证据进行融合。实验结果表明，该方法可有效地提高诊断的准确率，减少诊断的不确定性。

Application of evidence theory in fault diagnosis for transformer

In order to improve the accuracy of transformer fault diagnosis, a method of the evidence theory is applied. According to the characteristics data of transformer failure, the two parallel BP neural networks are used to carry on local fault diagnosis and acquire independent evidences each other, then the evidence theory was employed to fuse them. Experimental results show that the method is good to improve the reliability of the diagnosis and decrease the diagnostic uncertainty