BP网络在电力变压器故障诊断中的应用

以单隐层的BP组合神经网络在基于DGA的电力变压器故障诊断中的应用为例,在BP网络训练流程图的基础上,分别举例阐述了隐层节点个数、初始权值、训练误差、最大训练次数以及训练样本次序对网络训练效果和泛化能力的影响。指出这些因素的影响程度各不相同,具体应用时,可按照更改训练样本次序、调节隐层节点个数、初始权值、训练误差、训练次数的顺序依次更改网络的结构和相应的参数,以达到最佳的训练效果。

Application Study of BP Network Used in the Fault Diagnosis of Power Transformer

This paper taking one-hidden layer combined BP network model used in the fault diagnosis of power transformer as a exapmle and on the based of training flow process chart, points out that the number of hidden nodes, initial weight values, training error, the max training times and the order of training samples have different influence on the BP network generalization. In order to reach the best training result, it can be altered in the order of the order of training samples, the number of hidden nodes, the initial weight values, the training error and the max training times of BP network when using.