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计量学报  2019, Vol. 40 Issue (6): 980-985    DOI: 10.3969/j.issn.1000-1158.2019.06.07
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基于分群粒子群算法的平面度误差评定研究
毕立恒1,朱彦齐2
1. 黄河水利职业技术学院,河南 开封 453002
2. 开封技师学院,河南 开封 453002
Flatness Error Evaluation Based on Grouped Particle Swarm Optimization Algorithm
BI Li-heng1,ZHU Yan-qi2
1. Yellow River Conservancy Technical Institute, Kaifeng, Henan 453002, China
2. Kai Feng Institute of Technicians, Kaifeng, Henan 453002, China
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摘要 基于分群粒子群算法对平面度误差判定进行了研究。首先建立平面度误差评定数学模型,对平面度误差最小求解转化成对目标函数的非线性最优化问题;接着改进粒子群算法把粒子群一分为二,在不增加粒子个数和粒子维度的情况下,两个粒子群分别用来全局搜索和局部搜索,通过阈值判断早熟现象;最后给出了算法流程。实例验证结果表明:该算法具有较强的优化能力,对测试函数求解的最优解值数据波动性比较小,平面度的公差值为0.0073mm,相比LSM、DM、TPM、PSO、ABC算法公差值平均分别减少了0.0023mm,0.0025mm,0.0027mm,0.0002mm,0.0005mm,评定精度较高。
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毕立恒
朱彦齐
关键词 计量学平面度误差评定粒子群算法阈值    
Abstract:Flatness error is determined based on grouped particle swarm optimization(GPSO).Firstly,mathematic model of flatness error evaluation was established, and flatness error minimum was transmuted into nonlinear optimization problem of objective function.Secondly, GPSO was divided one PSO into two, which wasn't increased particle number and dimension, and one searched global, the other searched local, threshold was prevented premature.Finally, the process was given.The simulation results show that GPSO has a strong ability of optimization, and the optimal solution value of the test function is relatively small, the tolerance value of flatness is 0.0073mm, the average tolerances of GPSO are reduced 0.0023mm,0.0025mm,0.0027mm,0.0002mm and 0.0005mm comparing with LSM, DM, TPM, PSO and ABC,and the precision is higher than others algorithms.
Key wordsmetrology    flatness    error evaluation    particle swarm optimization    threshold
收稿日期: 2019-01-30      发布日期: 2019-10-10
PACS:  TB92  
  TP391  
基金资助:国家自然科学基金(61275154)
作者简介: 毕立恒(1973-),男,河南开封人,黄河水利职业技术学院讲师,硕士,研究方向为智能仪器仪表设计。Email:3065991303@qq.com
引用本文:   
毕立恒,朱彦齐. 基于分群粒子群算法的平面度误差评定研究[J]. 计量学报, 2019, 40(6): 980-985.
BI Li-heng,ZHU Yan-qi. Flatness Error Evaluation Based on Grouped Particle Swarm Optimization Algorithm. Acta Metrologica Sinica, 2019, 40(6): 980-985.
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