DocumentCode :
3201280
Title :
The Method of Solving Initial Configuration Unit of Probability in Product Self-Configuration Design
Author :
Bin, He
Author_Institution :
Huangshi Inst. of Technol., Huangshi, China
Volume :
3
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
852
Lastpage :
855
Abstract :
Starting with the introduction of product self-organization configuration design and configuration unit, the problem of solving initial configuration unit based on probability is described by using mathematic model of solving the problem in Fault Diagnose. Accordingly, fitness function is constructed for Genetic Algorithm on the basis of likelihood function. Meantime, vehicle leaf-spring is taken as an example to testify the solving process, where input design requirement and the corresponding probability value is given through the statistics of typical examples. The simulation process and result of solving initial configuration unit for leaf-spring is realized by helps of Genetic Algorithm tool in Matlab 7.1. Through the analysis of process and result, it can be concluded that the solving process is effective and reasonable, and the solving result accords nearly with actual situation of leaf-spring design, which prove that the solving method based on Genetic Algorithm is feasible to self-organization configuration design for vehicle leaf-spring.
Keywords :
fault diagnosis; genetic algorithms; product design; Genetic Algorithm; fault diagnosis; leaf spring design; probability; product initial configuration unit; product self configuration design; Algorithm design and analysis; Genetic algorithms; Mathematical model; Mathematics; Probability; Process design; Product design; Statistical analysis; Testing; Vehicles; Genetic Algorithm; initial configuration unit; product self-configuration design; vehicle leaf-spring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.275
Filename :
5523153
Link To Document :
بازگشت