基于模拟退火法与多层感知机的变压器故障诊断模型及其泛化性能研究
为诊断电力变压器内部的潜伏性故障,以溶解气体分析(DGA)数据为特征量,提出了一种基于多层感知机(MLP)的变压器故障诊断模型。以实际运行变压器的故障数据为学习样本,利用模拟退火法实现多层感知机内部节点之间的连接权重优化。以不同特征组合作为MLP的输入,对比、分析了MLP诊断故障类型的正确率;研究了MLP拓扑结构、参数正则化等对诊断模型泛化性能的影响。使用训练数据以外的变压器故障数据测试学习完成的诊断模型,获得较高的测试准确率。
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