Reliability-Based Design Optimization of Valve-Spring Using Evidence Theory and Genetic Algorithm

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The design optimization of valve-spring is achieved under the condition of expected reliability. The restrain conditions about the reliability of static strength and fatigue strength are considered, and then a dual-objective optimal problem of valve spring is modeled to obtain the lightest mass of valve-spring and the minimum error of spring stiffness. The feasibility of reliability condition is discussed based on evidence theory in order to improve the computational efficiency. By means of the combination of evidence, the upper and lower bounds of reliability are obtained, and a substituting model of restrain condition about reliability is proposed based on the obtained bounds of reliability. After the weighted combination of two objective functions is made, the optimization model is solved by using genetic algorithm. An example is given and it shows that the proposed method is effective.

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1258-1262

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August 2010

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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[1] Chen Lizhou, He Xiaofeng, Weng Haishan, et al. Optimization design methods of engineering random variables: principles and applications. Bejing: Science Press (1997).

Google Scholar

[2] A. P. Dempster. Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, Vol. 38, Issue 2, (February, 1967), pp.325-339.

DOI: 10.1214/aoms/1177698950

Google Scholar

[3] G. A. Shafer. Mathematical theory of evidence. Princeton: Princeton University Press (1976).

Google Scholar

[4] Huixin Guo, Guanyu Hu and Feng Tan. Evidence theory-based method and algorithm for calculation of reliability. Transactions of the Chinese Society for Agricultural Machinery. Vol. 39, Issue 5, (May, 2008), pp.128-132.

Google Scholar

[5] P. M. Zissimos and J. Zhou. A design optimization method using evidence theory. ASME Journal of Mechanical Design. Vol. 128, Issue 4, (July, 2006), pp.901-908.

Google Scholar

[6] Guo Huixin, Liu Deshun, Hu Guanyu, et al. Method of reliability design optimization using evidence theory and interval analysis. Chinese Journal of Mechanical Engineering. Vol. 44, Issue 12, (December, 2008), pp.35-41.

DOI: 10.3901/jme.2008.12.035

Google Scholar

[7] Li Bing, Zhu Meilin, Chen Xiaowei, et al. Optimization design of valve spring of engine based on genetic algorithms. Machine Design. Vol. 15, Issue 9, (1988), pp.22-23.

Google Scholar

[8] D. Dubois and H. Prade. Consonant approximations of belief functions. Int. J. Approximate reasoning. Vol. 4, Issue 5-6 , ( Sep. -Nov. 1999), pp.419-449.

DOI: 10.1016/0888-613x(90)90015-t

Google Scholar

[9] Liu Weixin. Machine optimization design. Beijing: Tsinghua University Press (1994).

Google Scholar