DocumentCode :
523741
Title :
Research of Optimal Structural Design for Mechanical Products Based on Data Mining
Author :
Tao, Jing ; Yin, Niandong ; Yan, Shenghua ; Wu, Qingming
Author_Institution :
Sch. of Mech. & Electron. Eng., Huangshi Inst. of Technol., Huangshi, China
Volume :
2
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
1047
Lastpage :
1050
Abstract :
Mechanical products normally consist of multi-parameter mechanisms. The uncertain factors resulted from the quantity of parameters and complicity of inter-relations shall give rise to problems of large dimensional arrays. Moreover, optimal models often contain functions of distinctive property, therefore feasible optimal methods are hard to find. On the basis of analyzing the optimal design methods and the data mining principles, a multi-level strategy of overall structural optimal design for mechanical products is put forth to bring out the structural optimal design rules of mechanical products based on the data mining principles which is demonstrated by the optimal structural design of the trolley frame of a gantry crane. The example shows that the data mining technology has fully tackled the issue of the optimal structural design of mechanical products.
Keywords :
data mining; optimisation; production engineering computing; structural engineering computing; data mining; distinctive property function; mechanical products; multiparameter mechanisms; optimal models; optimal structural design research; Data mining; Data processing; Design automation; Design methodology; Design optimization; Information filtering; Information filters; Intelligent structures; Mechanical products; Product design; data mining; multi-level strategy; optimal design; optimal models;
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.2010.827
Filename :
5522991
Link To Document :
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