Multiple ANNs combined scheme for fault diagnosis of power transformers

It is very important to find the incipient faults of power transformers for keeping away from the further deterioration in modern power system. For enhancing the accuracy of fault diagnosis for power transformers, a multiple ANNs scheme is proposed in this paper. In this scheme, a novel ANN method ELM is used to establish the base classifier for its good performance and fast learning speed. Secondly, the several base classifiers based on single ELM will be combined by consulting ensemble techniques. And then a multiple ELMs method is obtained. The real gas records data from a power company is used to establish fault diagnosis system for power transformers based on the new multiple ELMs method. For comparison, the conventional method and other ANN method are used to build fault diagnosis models by the same data. The experiments demonstrate the new multiple ELMs method has the best performance in both learning ability aspect and generalization ability aspect for fault diagnosis of power transformers.