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Dwell Time Algorithm Based on Bounded Constrained Least Squares Under Dynamic Performance Constraints of Machine Tool in Deterministic Optical Finishing
International Journal of Precision Engineering and Manufacturing-Green Technology ( IF 5.3 ) Pub Date : 2021-01-13 , DOI: 10.1007/s40684-020-00306-3
Yunfei Zhang , Fengzhou Fang , Wen Huang , Wei Fan

The dwell time algorithm is one of the most important techniques within the deterministic optical surfacing technologies. The existing dwell time algorithms are generally based on non-negative least squares (NNLS) without considering the dynamic performance constraints of machine tools. This is a circumstance that leads to poor convergence accuracy. In this paper, a dwell time algorithm, based on bounded constrained least-squares (BCLS) under dynamic performance constraints of the machine tool, has been developed. The upper and lower constraints of the dwell time model could be derived through the acceleration and deceleration mechanism of the CNC (Computer Numerical Control) machine tools. A two-metric projection Newton iteration algorithm was used to solve the large-scale dwell time model, which greatly improved the computation efficiency. The results of the experiments and simulations showed that the proposed algorithm will give a very high convergence accuracy for optical finishing with machine tools with different dynamic performances. When the machine acceleration was set to a value as low as 0.1 g, the accuracies of the surface figures PV (Peak-to-Valley) and RMS (Root Mean Square) till improved by 40.8% and 55.2%, respectively, when using the BCLS algorithm. The influences of different dynamic performances of the machine tools on the dwell time solutions have also been investigated, which will provide a good guidance in the design of deterministic polishing machine tools.



中文翻译:

确定性光学精加工中基于动态性能约束的有限有界最小二乘停留时间算法

停留时间算法是确定性光学表面技术中最重要的技术之一。现有的停留时间算法通常基于非负最小二乘(NNLS),而不考虑机床的动态性能约束。这是导致收敛精度差的情况。本文提出了一种基于动态性能约束的有限约束最小二乘(BCLS)的停留时间算法。停留时间模型的上限和下限可以通过CNC(计算机数控)机床的加减速机制来推导。采用二元投影牛顿迭代算法求解大规模停留时间模型,大大提高了计算效率。实验和仿真结果表明,该算法对于动态性能不同的机床光学精加工具有很高的收敛精度。当将机器加速度设置为低至0.1 g的值时,使用PFC时,表面图形PV(峰谷)和RMS(均方根)的精度分别分别提高了40.8%和55.2%。 BCLS算法。还研究了机床不同动态性能对停留时间解的影响,为确定性抛光机床的设计提供了很好的指导。当将机器加速度设置为低至0.1 g的值时,使用PFC时,表面图形PV(峰谷)和RMS(均方根)的精度分别分别提高了40.8%和55.2%。 BCLS算法。还研究了机床不同动态性能对停留时间解的影响,为确定性抛光机床的设计提供了很好的指导。当将机器加速度设置为低至0.1 g的值时,使用PFC时,表面图形PV(峰谷)和RMS(均方根)的精度分别分别提高了40.8%和55.2%。 BCLS算法。还研究了机床不同动态性能对停留时间解决方案的影响,这将为确定性抛光机床的设计提供良好的指导。

更新日期:2021-01-13
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