ITM Web Conf.
Volume 11, 20172017 International Conference on Information Science and Technology (IST 2017)
|Number of page(s)||6|
|Section||Session I: Computational Intelligence|
|Published online||23 May 2017|
A Method of Information Fusion Based on Fuzzy Neural Network and Its Application
1 Guizhou Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang, 550002 Guizhou, China
2 Wuhan Zhongyuan Huadian Science & Technology Co., Ltd, Wuhan 430074, China
In view of the limitation of fault diagnosis methods in substation intelligent patrol system, a fault diagnosis method based on multi-sensors information fusion is proposed. In the field of fault diagnosis, this method can deal with uncertain and imprecise information by using fuzzy theory, and has a high self-study capability based on neural network. Collecting samples of data through establishing many sensors in the scene of the intelligent patrol system, and then through the BP algorithm of fuzzy neural network training to achieve accurate fault diagnosis function of the intelligent patrol system. By comparing the result of an example, it shows that, compared with using single information, using multi-sensors information as the diagnosis method is more accurate and reliable in the intelligent patrol system.
© Owned by the authors, published by EDP Sciences, 2017
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