The temperature-variation fault diagnosis of high-voltage electric equipment based on information fusion

As high-voltage electric equipment has complex structure and works in harsh environment, FBG (fiber Bragg gating) sensors were applied to realize the real-time monitoring of some characters in which temperature was taken as the main factor. Using neural network to recognize and classify fault types, making a further fusion of fault information by expert system. After simulation and experiment, it shows good results, and provides a effective way to realize the monitoring and exact diagnosis of temperature-variation fault on high-voltage electric equipment.