Generating Machine-Optimal Numerical Control Paths

生成机器最优数控路径

• 批准号: 9912558
• 负责人: Sanjay Sarma
• 金额: $ 24.41万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9912558&HistoricalAwards=false
• 关键词: Generating; Machine; Optimal; Numerical; Control

The objective of this research is to generate the fastest tool paths to sweep a three-dimensional surface. This will be accomplished by first developing a mathematical formulation which captures all the practical constraints of machining, including motor speed limits, acceleration limits, surface finish requirements, machine kinematics and the effects of path discontinuities. It is likely that the formulated problem will not yield a closed-form solution. Several numerical approaches will be tested. A "greedy" approach has shown initial promise. In this approach, the tool paths are denerated using a local optimality criterion in place of the global optimality criterion. A second approach is to generate candidate tool path families are using parametric "basis" curves. A third approach which will be studied is a global search; the surface will be broken into smaller and smaller elemefltts, and tool paths directions will be varied individually in each element. The third approach is computationally expensive, but is also likely to yield the best results.If successful, this research will yield faster tools paths for high speed machining. As the spindle speeds available in CNC machine tools have increased, linear actuation systems have increasingly become the bottleneck in machining performance. Upgrading to faster linear motor technologies is very expensive. The tool paths enabled by this research will better utilize the capabilities of todays machine tool structures with new spindle technologies, and enable greater productivity without significantly greater costs.

这项研究的目标是生成扫描三维曲面的最快刀具路径。这将通过首先开发一个数学公式来实现，该公式捕获了加工的所有实际约束，包括电机速度限制、加速限制、表面光洁度要求、机床运动学和路径不连续的影响。公式化的问题很可能不会产生封闭形式的解。将对几种数值方法进行测试。一种“贪婪”的方法已经显示出初步的前景。在该方法中，用局部最优性准则代替全局最优性准则来退化刀具路径。第二种方法是使用参数“基本”曲线生成候选刀具轨迹族。将研究的第三种方法是全局搜索；曲面将被分解成越来越小的元素，并且刀具路径方向将在每个元素中单独改变。第三种方法计算昂贵，但也可能产生最好的结果。如果成功，这项研究将为高速加工提供更快的刀具路径。随着数控机床主轴转速的提高，直线驱动系统越来越成为影响加工性能的瓶颈。升级到更快的直线电机技术是非常昂贵的。通过这项研究实现的刀具路径将更好地利用当今采用新主轴技术的机床结构的能力，并在不显著增加成本的情况下实现更高的生产率。