基于混合搜索算法的圆度误差评定

Roundness Error Evaluation Based on Hybrid Search Algorithm

加工中因各种因素导致回转类零件产生几何误差,而圆度误差作为重要的几何误差直接影响机器配合精度与性能,因此,准确评定零件的圆度误差显得格外重要。本文提出一种精确评估圆度误差的混合方法,由区域搜索算法和三角形搜索算法两部分组成。区域搜索算法用于区域的全局搜索,找到准圆心,再运用三角形搜索算法,根据限制条件进行精细搜索,找到最小包容区域圆心完成圆度误差评定。本方法无需满足小误差和小偏差假设,对采样点数与采样策略没有要求。通过仿真验证了本文方法的可行性,并对实例验证与试验验证进行评定与比较。结果表明,本方法比PSO算法和文献中的算法评定精度更高,不存在模型误差与原理误差,对采样点分布与数量没有限制,可以准确找到最小包容区域圆心。

The roundness error as an important geometric error directly affects the accuracy and performance of machine fits,so it is particularly important to accurately assess the roundness error of parts due to various factors in the machining of rotary-type parts.This paper proposes a hybrid method to accurately evaluate roundness error,which consists of two parts:area search algorithm and triangle search algorithm.The area search algorithm is used to conduct a global search of the area to find the quasi-circular center,and then the triangle search algorithm is used to conduct a fine search according to the constraints,and finally find the minimum inclusive area center to complete the roundness error evaluation.This method does not need to meet the assumption of small error and small deviation,and there is no requirement for sampling points and sampling strategy.The feasibility of the method is verified by simulation,and the results show that the method is more accurate than the PSO algorithm and the algorithm in the literature,and there is no model error and principle error,and there is no restriction on the distribution and number of sampling points,and the minimum inclusive area center can be found accurately.