• CN:11-2187/TH
  • ISSN:0577-6686

›› 2005, Vol. 41 ›› Issue (11): 158-162.

• 论文 • 上一篇    下一篇

基于遗传算法的超精密切削表面粗糙度预测模型参数辨识及切削用量优化

卢泽生;王明海   

  1. 哈尔滨工业大学机电工程学院
  • 发布日期:2005-11-15

PREDICTIVE MODELING OF SURFACE ROUGHNESS AND CUTTING PARAMETERS OPTIMIZATION IN ULTRA-PRECISION TURNING BASED ON GENETIC ALGORITHM

Lu Zesheng;Wang Minghai   

  1. College of Mechanical and Electronical Engineering, Harbin Institute of Technology
  • Published:2005-11-15

摘要: 建立易于分析各切削用量对粗糙度影响关系的表面粗糙度预测模型和最优的切削用量组合,是超精密切削加工技术的不断发展的需要。针对最小二乘法和传统优化方法的不足,提出了将遗传算法用于超精密切削表面粗糙度预测模型的参数辨识,并用于求解最优切削用量,给出了金刚石刀具超精密切削铝合金的表面粗糙度预测数学模型和切削用量优化结果,进行了遗传算法和常规优化算法的比较,结果表明遗传算法较最小二乘法和传统的优化方法更适合于粗糙度预测模型的参数辨识及保证切削用量的最优。

关键词: 表面粗糙度预测模型, 超精密切削, 遗传算法, 优化

Abstract: In ultra-precision turning process, the modeling of surface roughness and the optimization of cutting parameters are the key factors to improve the quality of products and rise the efficiency of equipment. The accurate prediction of surface roughness and optimal cutting parameters are urgently required with the progress in ultra-precision manufacturing. To meet the requirement, the application of genetic algorithm for the surface roughness prediction model and cutting parameters optimization in ultra-precision turning is proposed by a practical example. Mathematics model is introduced and optimal results are given. The prediction model and optimal cutting parameters using genetic algorithm are compared with least square method and traditional optimal results. Comparison shows that genetic algorithm is more suitable than traditional optimal methods in terms of modeling and guaranteeing prediction accuracy and cutting parameters optimization.

Key words: Cutting parameters, Genetic algorithm, optimization, Surface roughness prediction model, Ultra-precision turning

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