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

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3 Author(s)
Yong-Wei Li ; Coll. of Electr. Eng. & Inf. Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang ; Xing-De Han ; Zhen-Yu Wang

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.

Published in:

Machine Learning and Cybernetics, 2008 International Conference on  (Volume:1 )

Date of Conference:

12-15 July 2008