Optimal localization of complex surfaces in CAD-based inspection

Complex surface inspection requires the optimal localization of the measured surface related to the design surface so that the two surfaces can be compared in a common coordinate frame. This paper presents a new technique for solving the localization problem. The basic approach consists of two steps: 1) rough localization of the measured points to the design surface based on curvature features, which can produce a good initial estimate for the optimal localization; 2) fine localization based on the least-square principle so that the deviation between the measured surface and the design surface is minimized. To efficiently compute the closest points on the design surface of the measured points, a novel method is proposed. Since this approach does not involve an iterative process of solving non-linear equations for the closest points, it is more convenient and robust. The typical complex surface is used to test the developed algorithm. Analysis and comparison of experimental results demonstrate the validity and applicability of the algorithm.