DocumentCode
1983065
Title
Auto-identification of BP neural network in defective product of shock absorber
Author
Xie, Weidong ; Ren, Qiang ; Shen, Jisheng
Author_Institution
Inst. of Vehicular Eng., Zhejiang Univ. of Technol., Hangzhou, China
fYear
2011
fDate
16-18 Sept. 2011
Firstpage
4744
Lastpage
4747
Abstract
Indicator diagram of shock absorber plays an important role in identifying whether it is qualified. At present, shape identification of the indicator diagram of shock absorber depends heavily on experience. The paper discusses the process BP neural network identify kinds of indicator diagrams of shock absorber, including the algorithm of BP neural network, the method of picking up characteristics of the indicator diagram of shock absorber and some successful examples.
Keywords
backpropagation; mechanical engineering computing; neural nets; shock absorbers; BP neural network; backpropagation; indicator diagram; shape identification; shock absorber defective product; Artificial neural networks; Educational institutions; Electrical engineering; Expert systems; Servomotors; Shape; Shock absorbers; BP neural network; indicator diagram; shape identification; shock absorber;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Control Engineering (ICECE), 2011 International Conference on
Conference_Location
Yichang
Print_ISBN
978-1-4244-8162-0
Type
conf
DOI
10.1109/ICECENG.2011.6057512
Filename
6057512
Link To Document