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A Minimum Zone Method for Evaluating Perpendicularity Errors of Planar Lines Based on PSO Algorithm

According to characteristics of perpendicularity error evaluation of planar lines, Particle Swarm Optimization (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, it can find the global optimal solution, and the precision of calculating result is very good. Then, the objective function calculation approaches for using the Particle Swarm Optimization 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 does provide better accuracy on perpendicularity error evaluation, and it has fast convergent speed as well as using computer and popularizing application easily.