One intelligent method for fault diagnosis and its application

An intelligent method for fault diagnosis of a transformer is discussed based on chromatogram data, and a model of improved neural networks for fault synthesis diagnosis is presented. We have tested and verified the practical data of fault samples. Experiments prove that this method is practically variable, has a high recognition rate of faults and can be applied to the fault diagnosis of other electric equipment.