基于爬山遗传算法的三坐标测量路径优化

doi:10.3969/j.issn.1000-1158.2016.03.03

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Abstract Aiming at the problem of slow convergence speed and premature convergence in using the genetic algorithm to conduct the measuring path optimization in Coordinate Measuring Machine, the path optimization algorithm in Coordinate Measuring Machine based on Hill-climbing Genetic Algorithm was proposed. According to characteristics of the path optimization in Coordinate Measuring Machine, the mathematic model of the measuring path optimization was built and the parameters of coding, initial group, selection, cross for measuring path optimization problems were constructed. In addition, the climbing was added to increase convergence speed of the genetic algorithm for the global optimal solution. Besides, the simulation was programmed to verify the effectiveness of the Hill-climbing Genetic Algorithm and the application examples were used. Results show that when using the Hill-climbing Genetic Algorithm to conduct the path optimization algorithm in Coordinate Measuring Machine, the local optimization ability of genetic algorithm and the convergence speed were improved and the very good optimal solution was obtained. Therefore, the measuring efficiency was improved.

Key words： metrology CMM optimization of measuring path GA HCGA

Received: 13 July 2015 Published: 22 March 2016

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TB92

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	Articles by authors
	WU Feng-he
	SUN Ying-bing
	WANG Xin

Cite this article:

WU Feng-he,SUN Ying-bing,WANG Xin. Path Planning Method Based on HCGA in Coordinate Measuring Machine[J]. Acta Metrologica Sinica, 2016, 37(3): 235-240.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2016.03.03 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2016/V37/I3/235

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