基于天牛须改进粒子群算法的平面度误差评定研究

doi:10.3969/j.issn.1000-1158.2021.01.02

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摘要基于天牛须改进粒子群算法(BAS-PSO)对平面度误差进行了评定研究。首先,建立基于最小区域的平面度误差评定的数学模型,并将目标函数转化为非线性最优化问题;接着,在粒子群算法(PSO)的基础上,引入局部搜索能力较强的天牛须算法(BAS),加速全局搜索和局部搜索的并行计算,避免算法早熟收敛并陷入局部最优,提高平面度误差评定的精度和效率;最后,通过Rosenbrock和Schaffer测试函数,验证BAS-PSO的有效性,采用BAS-PSO对目标函数进行求解。实验结果表明该算法相对于BAS和PSO均取得较好的寻优效果。将该算法应用到平面度误差实例测量中,得出平面度公差值为0.00615mm;相比最小二乘法(LSM)、遗传算法(GA)、BAS和PSO算法,公差值分别减少了0.0023mm,0.00127mm,0.00058mm,0.00037mm;验证了该算法的可行性及优越性。

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	刘超
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关键词 ：计量学, 平面度误差, 天牛须搜索, 粒子群算法, 误差评定

Abstract：A particle swarm optimization algorithm based on the beetle antennae search algorithm (BAS-PSO) is proposed to evaluate flatness errors. Firstly, a mathematical model for evaluating the flatness error based on the minimum region is established and the objective function is transformed into a nonlinear optimization problem. Secondly, on the basic of particle swarm optimization algorithm (PSO), the beetle antennae search algorithm (BAS) with strong global search ability is introduced. As a result, the parallel computation of global search and local search is sped up to avoid premature convergence and falling into local optimization, and the accuracy and efficiency of flatness error evaluation is improved. Finally, the effectiveness of BAS-PSO is experimented by Rosenbrock and Schaffer test functions, BAS-PSO is used to solve the objective function based on the evaluation mathematical model of flatness error of the minimum region, the experimental results show that the algorithm is better than BAS and PSO. The algorithm was applied to the sample measurement of flatness error, the tolerance value of flatness is 0.00615mm, the average tolerances of BAS-PSO are reduced 0.0023mm, 0.00127mm, 0.00058mm, and 0.0037mm compering with the least square method (LSM), genetic algorithm (GA), BAS, and PSO, which verified the feasibility and superiority of the algorithm.

Key words： metrology flatness error BAS PSO algorithm error evaluation

收稿日期: 2020-04-13 发布日期: 2021-01-19

PACS:

TB92

基金资助:国家科技重大专项(2018ZX04027001);教育部人文社科项目(20YJCZH150);湖北省教育厅科学技术项目(Q20181801);汽车动力传动与电子控制湖北省重点实验室基金(ZDK1201703);湖北汽车工业学院博士基金(BK201905);湖北汽车工业学院大学生创新项目(DC2019012)

作者简介: 刘超(1995-),男,湖北十堰人,湖北汽车工业学院硕士研究生,研究方向为智能制造与机器视觉。Email: 201911038@huat.edu.cn

引用本文:

刘超,王宸,钟毓宁. 基于天牛须改进粒子群算法的平面度误差评定研究[J]. 计量学报, 2021, 42(1): 9-15.
LIU Chao,WANG Chen,ZHONG Yu-ning. A Particle Swarm Optimization Algorithm Based on Beetle Antennae Search for Flatness Error Evaluation. Acta Metrologica Sinica, 2021, 42(1): 9-15.

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