Abstract

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.

Details

Title
A Method of Information Fusion Based on Fuzzy Neural Network and Its Application
Author
Ji-Pu, Gao; Chang-Bao, Xu; Zhang, Li; Jun-Lin, Zheng; Shu, Huai; Yuan, Xi
Section
Session I: Computational Intelligence
Publication year
2017
Publication date
2017
Publisher
EDP Sciences
ISSN
24317578
e-ISSN
22712097
Source type
Conference Paper
Language of publication
English
ProQuest document ID
2058863757
Copyright
© 2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.