Application of improved differential evolution algorithm in flatness evaluation of large work-piece

Yu-kang LI; Hai-hong HUANG

doi:10.3788/OPE.20192712.2659

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Application of improved differential evolution algorithm in flatness evaluation of large work-piece

Micro/Nano Technology and Fine Mechanics | 更新时间：2020-07-09

- Application of improved differential evolution algorithm in flatness evaluation of large work-piece
- Optics and Precision Engineering Vol. 27, Issue 12, Pages: 2659-2667(2019)
- 作者机构：
  
  1.机械工业绿色设计与制造重点实验室，安徽合肥 230009
  2.合肥工业大学机械工程学院，安徽合肥 230009
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20192712.2659
  CLC： TP241
- Received：18 April 2019，
  
  Accepted：26 June 2019，
  
  Published：25 December 2019
- 稿件说明：
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Yu-kang LI, Hai-hong HUANG. Application of improved differential evolution algorithm in flatness evaluation of large work-piece[J]. Optics and precision engineering, 2019, 27(12): 2659-2667.
DOI：

Yu-kang LI, Hai-hong HUANG. Application of improved differential evolution algorithm in flatness evaluation of large work-piece[J]. Optics and precision engineering, 2019, 27(12): 2659-2667. DOI： 10.3788/OPE.20192712.2659.

摘要

生产线上检测大型复杂工件平面度误差时，存在检测面积较大、数据量较多的问题，为了提高检测效率及精度，采用优化算法提高其平面度误差评定速度。提出将差分进化(DE)算法应用在其平面度误差的评定中，并提出将粒子群(PSO)算法的优化方法融入差分进化算法的框架，改进变异操作以提高标准DE算法的收敛速度。介绍了大型工件平面度误差评定采用最小区域法的数学模型，阐述了改进的DE算法的原理和实现步骤，最后以叉车外壁板为例，通过对外壁板平面度误差的评定以验证算法的收敛速度与精度。结果表明，改进的DE算法在大型工件平面度误差评定中收敛结果稳定，误差接近于0；精度较遗传算法提高36.83%；收敛速度较遗传算法提高58.33%，较标准的DE算法提高28.57%。可以很好地应用在大型工件平面度误差检测中，提高检测效率。

Abstract

Several problems are encountered when measuring the flatness error of large and complex workpieces in a production line

such as abroad area of the detection surface and a vast amount of data. To improve the efficiency and accuracy of flatness error detection

an optimization algorithm was adopted to increase the speed of flatness error evaluation. The Differential Evolution (DE)algorithm was implemented for solving these problems

and the optimization method of Particle Swarm Optimization(PSO) algorithm was integrated into the DE algorithm framework to increase the convergence speed by improving the mutation operation. This study proposed a mathematical model using the minimum zone method for the flatness error evaluation of large workpieces and expounded the principle and implementation steps of the improved DE algorithm. Finally

using the outer panel of a forklift truck as an example

the convergence speed and accuracy of the algorithm were verified by evaluating the flatness error of the outer panel. The results demonstrate that the convergence result of the improved DE algorithm is stable for evaluating the flatness error of large workpieces

and the error is close to zero. The accuracy of the proposed algorithm is 36.83% higher than that of the genetic algorithm

and the convergence speed is 58.33% and 28.57% higher than those of the genetic algorithm and standard DE algorithm

respectively. The proposed algorithm can be satisfactorily applied to the flatness error detection of large workpieces to improve the detection efficiency.

关键词

Keywords

references

雷贤卿, 李飞, 涂鲜萍, 等.评定平面度误差的几何搜索逼近算法[J].光学精密工程, 2013, 21(5): 1312-1317.

LEI X Q, LI F, TU X P, et al .. Geometry searching approximation algorithm for flatness error evaluation[J]. Opt. Precision Eng ., 2013, 21(5): 1312-1317.(in Chinese)

温英明, 温文炯.最小包容区域法评定平面度误差的程序设计[J].工具技术, 2014, 48(8): 136-140.

WEN Y M, WEN W J. Designing program for measuring departure with minimum zone from flatness[J]. Tool Technology , 2014, 48(8): 136-140.(in Chinese)

温秀兰, 宋爱国.改进遗传算法及其在平面度误差评定中的应用[J].应用科学学报, 2003, 21(3): 221-224.

WEN X L, SONG A G. The application of improved genetic algorithm based on real coding in flatness error evaluation[J]. Journal of Applied Sciences , 2003, 21(3): 221-224.(in Chinese)

杨健, 赵宏宇.浮点数编码改进遗传算法在平面度误差评定中的研究[J].光学精密工程, 2017, 25(3):706-711.

YANG J, ZHAO H Y. The research of floating-point coding improved genetic algorithm flatness error evaluation[J]. Opt. Precision Eng ., 2017, 25(3): 706-711.(in Chinese)

罗钧, 王强, 付丽.改进蜂群算法在平面度误差评定中的应用[J].光学精密工程, 2012, 20(2): 422-429.

LUO J, WANG Q, FU L. Application of modified artificial bee colony algorithm to flatness error evaluation[J]. Opt. Precision Eng ., 2012, 20(2): 422-429.(in Chinese)

崔长彩, 张耕培, 傅师伟, 等.利用粒子群优化算法的平面度误差评定[J].华侨大学学报(自然科学版), 2008, 29(4): 507-509.

CUI CH C, ZHANG G P, FU SH W, et al .. Particle swarm optimization-based flatness evaluation[J]. Journal of Huaqiao University : Natural Science , 2008, 29(4): 507-509.(in Chinese)

姜伟, 王宏力, 何星, 等.基于适应度反馈作用的PSO算法改进[J].计算机工程, 2012, 38(22):146-150.

JIANG W, WANG H L, HE X, et al .. Improvement of PSO algorithm based on fitness feedback effect[J]. Computer Engineering , 2012, 38(22): 146-150.(in Chinese)

FAN Q, YAN X. Self-adaptive differential evolution algorithm with discrete mutation control parameters[J]. Expert Systems with Applications , 2015, 42(3): 1551-1572.

张泉, 尹达一, 魏传新.大口径压电快摆镜机构迟滞非线性补偿与控制[J].红外与激光工程, 2019, 48(2):178-185.

ZHANG Q, YIN D Y, WEI CH X. Hysteresis nonlinear compensation and control for large-aperture piezoelectric fast steering mirror[J]. Infrared and Laser Engineering , 2019, 48(2):178-185.(in Chinese)

MALLIPEDDI R, SUGANTHAN PN, PAN QK, et al .. Differential evolution algorithm with ensemble of parameters and mutation strategies[J]. Applied Soft Computing , 2011, 11(2):1679-1696.

WANG Y, CAI Z, ZHANG Q. Differential evolution with composite trial vector generation strategies and control parameters[J]. IEEE Trans. on Evolutionary Computation , 2011, 15(1):55-66.

唐亚, 王振友.一种基于进化方向的新的差分进化算法[J].计算机系统应用, 2016, 25(10):146-153.

TANG Y, WANG ZH Y. An evolution direction-based mutation strategy for differential evolution algorithm[J]. Computer Systems Applications , 2016, 25(10):146-153.(in Chinese)

KANAD T, SUZUKI S. Evaluation of minimum zone flatness by means of nonlinear optimization techniques and its verification[J]. Prec Eng , 1993, 15(2):93-99.

VESTERSTROM J, THOMSEN R. A comparative study of differential evolution, particle swarm optimization and evolutionary algorithms on numerical benchmark problems[C]. Congress on Evolutionary Computation , 2004: 1980-1987.

RAINER S, KENNETH P. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of global optimization , 1997, 11(4):341-359.

王贞艳, 贾高欣.压电陶瓷作动器非对称迟滞建模与内模控制[J].光学精密工程, 2018, 26(10):2484-2492.

WANG ZH Y, JIA G X. Asymmetric hysteresis modeling and internal model control of piezoceramic actuators[J]. Opt. Precision Eng ., 2018, 26(10):2484-2492.(in Chinese)

崔长彩, 车仁生, 罗小川, 等.基于实数编码遗传算法的平面度评定[J].光学精密工程, 2002, 10(1):36-40.

CUI CH C, CHE R SH, LUO X CH, et al .. Flatness evaluation based on real coded genetic algorithm[J]. Opt. Precision Eng ., 2002, 10(1):36-40.(in Chinese)

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