DocumentCode
3394851
Title
Transformer failure diagnosis based on BP neural network
Author
Zhang Yongtao ; Wang Yajuan ; Zhao Yanjun ; Wu Lan ; Zhen Pengjie
Author_Institution
Coll. of Electr. Eng., Hebei United Univ., Tangshan, China
fYear
2011
fDate
19-22 Aug. 2011
Firstpage
1445
Lastpage
1448
Abstract
A BP network model for transformer fault diagnosis is established based on the MATLAB environment in this paper. A large number of data samples are collected and tested, L_M algorithm is used for training samples and simulation in network model. The actual output is gained and made comparative study with the expected output. Finally, it confirms that this network model has a high accuracy and can be used for transformer fault diagnosis.
Keywords
backpropagation; fault diagnosis; mathematics computing; neural nets; BP neural network; L_M algorithm; MATLAB environment; data samples; transformer failure diagnosis; Biological neural networks; Educational institutions; Fault diagnosis; MATLAB; Mathematical model; Neurons; Training; BP neural network; MATLAB simulation; artificial Intelligence; failure diagnosis; transformer;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location
Jilin
Print_ISBN
978-1-61284-719-1
Type
conf
DOI
10.1109/MEC.2011.6025743
Filename
6025743
Link To Document