A Minimum Zone Method for Evaluating Straightness Errors Using PSO Algorithm

• Published in: Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues Vol. 5226; pp. 308 - 314
• Main Author: Zhang, Ke
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2008; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Evaluating Straightness; Genetic Algorithms (GA); PSO Algorithm
• ISBN: 3540874402; 9783540874409
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-87442-3_39

Straightness error is the commonest one of form errors. In this paper, an intelligent evaluation method for straightness errors is provided. According to characteristics of straightness error evaluation, Particle Swarm Optimization (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process for using the PSO to evaluate minimum zone error are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, PSO algorithm can find the global optimal solution, and the precision of calculating result is very good. Compared to genetic algorithms (GA), PSO is easy to implement and there are few parameters to adjust. Finally, a numerical example is carried out. The control experiment results evaluated by using different method such as the least square, simplex search, Powell optimum methods, Simulated Annealing Algorithms (SAA), GA and PSO, indicate that the proposed method does provide better accuracy on straightness error evaluation, and it has fast convergent speed as well as using computer.