Title: Study on evaluation of perpendicularity errors with an improved particle swarm optimisation for planar lines

Authors: Ke Zhang; Shengze Wang

Addresses: School of Mechanical Engineering, Shanghai Institute of Technology, 100 Haiquan Road, Shanghai, China ' College of Mechanical Engineering, Donghua University, 1882 West Yanan Road, Shanghai, China

Abstract: According to characteristics of perpendicularity error evaluation of planar lines, an improved particle swarm optimisation (PSO) is proposed to evaluate the minimum zone error. The evolutional optimum model and the calculation process are introduced in detail. Compared with conventional optimum methods such as simplex search and Powell method, PSO can find the global optimal solution, and the precision of calculating result is very good. Compared to other intelligence computation algorithms such as genetic algorithm (GA), PSO is easier to carry out with fewer parameters to adjust. Then, the objective function calculation approaches for using the particle swarm optimisation algorithm to evaluate minimum zone error are formulated. Finally, the control experiment results evaluated by different method such as the least square, simplex search, Powell optimum methods and genetic algorithm (GA), indicate that the proposed method can provide better accuracy on perpendicularity error evaluation effectively, and is well suited for position error evaluation.

Keywords: metrology; perpendicularity errors; minimum zone error; particle swarm optimisation; PSO; planar lines; position errors.

DOI: 10.1504/IJMIC.2013.051934

International Journal of Modelling, Identification and Control, 2013 Vol.18 No.1, pp.54 - 60

Available online: 05 Feb 2013 *

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