DocumentCode :
3364617
Title :
Application of BP neural network in welding joint data processing
Author :
Liu Yuan-peng ; Wen Zhen-hua
Author_Institution :
Dept. of Mech. & Electr. Eng., Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
Volume :
5
fYear :
2011
fDate :
12-14 Aug. 2011
Firstpage :
2612
Lastpage :
2614
Abstract :
This article gathered the welding current, welding voltage and column displacement moves parameters of the U71Mn rail welding process orthogonal test, and extracted the quality characteristic quantities of luminous time ratio, energy input, weld period and cremation quantity before accelerating preceding to input to the BP neural network forecast model to research the welding process research to the U71Mn rail. The test result indicated that the welding process parameter conformed to the railroad standard stipulation, and played certain instruction role in the project practical application.
Keywords :
backpropagation; construction components; electric welding; neural nets; production engineering computing; railways; BP neural network; U71Mn rail welding process; column displacement; cremation quantity; energy input; luminous time ratio; welding current; welding joint data processing; welding voltage; Forecasting; Joints; Rails; Shape; Training; Transfer functions; Welding; BP; data processing; neural network; welding joint;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang, China
Print_ISBN :
978-1-61284-087-1
Type :
conf
DOI :
10.1109/EMEIT.2011.6023633
Filename :
6023633
Link To Document :
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