基于最小区域法评定方法中,存在对零件进行数据提取时其摆放位置会影响优化结果和多采样点求解繁琐局部收敛等问题,研究了最小区域圆柱度误差评定新方法。首先,建立了最小区域评定数学模型;然后,进行空间坐标变换投影,将圆柱体任意位置数据点转化为固定位置,将空间多采样点问题转换为平面进行特征点提取;最后,建立内外扫描区域和进行坐标轴线的更替,并对优化结果进行复核,实现有效防止出现局部最优解。实例检验结果表明:对数据样本最多的数据集,计算效率提高了1.5倍,可有效处理多采样点和任意位置采样点的圆柱度误差,且随着数据集样本点的增加计算效率提升越显著,具有较高的求解稳定性。
Abstract
For the minimum zone method based on the evaluation method, there are problems such as the placement of parts will affect the optimization results when the data extraction of parts is performed and the cumbersome local convergence of the multi-sampling point solution,a new method for evaluating the cylindricity error in the minimum zonen is studied. First, the minimum zone evaluation mathematical model is established. Then, the spatial coordinate transformation projection is carried out to transform the data points of any position of the cylinder into a fixed position, and the spatial multi-sampling point problem is converted into a plane for feature point extraction. Finally, the internal and external scanning area and the replacement of coordinate axes are set up and the results of optimization are reviewed to achieve effective prevention of local optimal solutions. The example test results show that for the dataset with the largest number of data samples, the computational efficiency is improved by 1.5 times, which can effectively handle the cylindricity error of multi-sampling points and sampling points at arbitrary position. Moreover, as the number of sample points in the dataset increases, the computational efficiency improves more significantly, and the solution has a high stability.
关键词
计量学 /
圆柱度;坐标变换投影;特征点提取;最小区域评定 /
内外扫描区域
Key words
metrology /
cylindricity /
coordinate transformation projection /
feature point extraction /
minimum zone evaluation /
inner and outer scanned zone
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