Transformer Fault Diagnosis Based Extension Neural on Networks
Zhng Wei-hua · Journal of Jiangxi Vocational and Technical College of Electricity · 2009
There is a problem that the training rule and classifying rule is not consistent when the mostly used BP neural network is applied in the transformer fault diagnosis.It causes recognition rate of samples to reduce and network training slow.By extension transform,using a region in the outputting space replaces apoint,then using the extension neural network in the transformer fault diagnosis.The example proves the training speed is extraordinarily improved and the problem of inconsistent training rule and classifying rule is solved.