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采用遗传算法优化加工夹具定位和加紧位置

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采用遗传算法优化加工夹具定位和加紧位置(中文4400字,英文2800字)
摘要
工件变形的问题可能导致机械加工中的空间问题。支撑和定位器是用于减少工件弹性变形引起的误差。支撑、定位器的优化和夹具定位是最大限度的减少几何在工件加工中的误差的一个关键问题。本文应用夹具布局优化遗传算法(GAs)来处理夹具布局优化问题。遗传算法的方法是基于一种通过整合有限的运行于批处理模式的每一代的目标函数值的元素代码的方法,用于来优化夹具布局。给出的个案研究说明已开发的方法的应用。采用染色体文库方法减少整体解决问题的时间。已开发的遗传算法保持跟踪先前的分析设计,因此先前的分析功能评价的数量降低大约93%。结果表明,该方法的夹具布局优化问题是多模式的问题。优化设计之间没有任何明显的相似之处,虽然它们提供非常相似的表现。
关键词:夹具设计;遗传算法;优化

Machining fixture locating and clamping position optimization using genetic algorithms
Necmettin Kaya
Abstract
Deformation of the workpiece may cause dimensional problems in machining. Supports and locators are used in order to reduce the error caused by elastic deformation of the workpiece. The optimization of support, locator and clamp locations is a critical problem to minimize the geometric error in workpiece machining. In this paper, the application of genetic algorithms (GAs) to the fixture layout optimization is presented to handle fixture layout optimization problem. A genetic algorithm based approach is developed to optimise fixture layout through integrating a finite element code running in batch mode to compute the objective function values for each generation. Case studies are given to illustrate the application of proposed approach. Chromosome library approach is used to decrease the total solution time. Developed GA keeps track of previously analyzed designs; therefore the numbers of function evaluations are decreased about 93%. The results of this approach show that the fixture layout optimization problems are multi-modal problems. Optimized designs do not have any apparent similarities although they provide very similar performances.
Keywords: Fixture design; Genetic algorithms; Optimization

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