According to geometric definition of the sphericity,a novel evaluation method which named as geometry search approaching method for sphericity error is presented. Firstly,an initial reference point is taken as a datum point and built a regular hexahedron and established an auxiliary points. Secondly,the each auxiliary points and the datum point are used as the centre of the measured sphere to calculate the radius of all measured points. And then modify the side length of the hexahedron or the position of the reference point by comparing these radius extreme differences. Finally,by repeating this process,the minimum zone containing all measurement points is obtained and the minimum zone evaluation for the measured spherical surface is implemented. The method is used to process a group of metrical data,and the results indicate that the sphericity error value from this algorithm can be reduced by 0. 6μm as compared with least square method,and are consistent with the results obtained by the analytic method and evolutionary computation method. The results show that the algorithm can get not only the minimum zone solution accurately but also has good stability.%结合球度误差的几何定义，提出了一种基于几何搜索的球度误差最小区域评价方法。首先，以初始参考点为基准，布置一定边长的正方体，依次以正方体的每个顶点为假定理想球心计算所有测量点的半径值，通过比较判断，调整正方体的位置及边长，最终获得包容所有测点的最小区域，实现球度的最小区域评定。在终止搜索条件为0.00001 mm 时，对同一组测量数据，该算法的结果比最小二乘法减小了0.6μm，并与解析法、遗传算法的结果相一致。计算过程及结果表明，该算法不仅能准确地得到最小区域解，而且计算结果有良好的稳定性。
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