DocumentCode :
2982955
Title :
The Fault Diagnosis Research Based on SOM-BP Composite Neural Network Learning Algorithm
Author :
Song Yu ; Wang Fengxia ; Yi Lu
Author_Institution :
Coll. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
fYear :
2012
fDate :
7-9 Dec. 2012
Firstpage :
535
Lastpage :
539
Abstract :
Introduce the basic principle and learning algorithm of the SOM network and BP network. The diagnosis mode is established with the common breakdown condition and the related parameters of the gear boxes used as the training sample. Due to the complex nonlinear relation between breakdown mode and characteristic parameters of gear-boxes, the SOM-BP composite neural net work is used. First have a preliminary pattern recognition classification for training samples by SOM network and details of fault classification by BP network under the MATLAB 7.1 environment, through the simulation test and comparison with BP network, reliability of the composite neural network for gear box failure diagnosis are verified.
Keywords :
backpropagation; fault diagnosis; mechanical engineering computing; power transmission (mechanical); self-organising feature maps; MATLAB 7.1 environment; SOM-BP composite neural network learning algorithm; breakdown condition; fault classification; fault diagnosis research; gear box failure diagnosis; pattern recognition classification; Biological neural networks; Educational institutions; Fault diagnosis; Neurons; Training; Vectors; composite neural network; fault diagnosis; simulation and test;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
Type :
conf
DOI :
10.1109/ICCECT.2012.103
Filename :
6413773
Link To Document :
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