SPHERICITY ERROR EVALUATION BASED ON 3D OPTICAL MEASUREMENT

Sphericity is an important geometrical feature in modern industry. Most of the former sphericity evaluation is studied based on 2D measurement, because 3D measurement is complex and with high cost. But it is reported that 2D sphericity evaluation method is unreasonable. In order to evaluate sphericity error accurately and effectively, this paper proposes novel 3D sphericity error evaluation method based on SFS technique. If a sphere is placed under SFS vision system, its 3D shape will be recovered from 0° to 180° only by one sphere image. Each pixel in the image represents a 3D data in the sphere. All these 3D data can be used in the sphericity evaluation procedure. Least-square method (LSM), minimum circumscribed sphere, maximum inscribed sphere, and minimum zone solution, which commonly used in sphericity evaluation, are all studied in this paper. Compared with the conventional sphericity evaluation based on 2D measurement, the proposed 3D evaluation has the merits of noncontact, non-destructive, low cost, high speed, and high reliable. 3D shape recovery of a sphere based on SFS and its 3D sphericity evaluation procedure will be analyzed in this paper.