Sampling Strategy for Free-Form Surface Inspection Using Coordinate Measuring Machines

Due to the complexity and non-rotational symmetry of free-form surface, it is difficult to achieve accurate and efficient inspection method. In order to solve this problem, three types of sampling sequences are proposed to specify a set of measuring points of free-form surface. For comparing the results of different sampling strategies, the profile errors of free-form surface are calculated based on a quasi particle swarm optimization (QPSO) searching the transformation parameters to implement localization and surface subdivision method finding the closest points on the design model corresponding to measured points. In order to obtain effective sampling strategies, four design models are generated by non-uniform rational basis spline (NURBS) and parts are manufactured on two machining centers to obtain surfaces of different roughness and measured on CMMs by selecting different sampling methods and sample sizes. The profile errors of parts are calculated by the proposed method and CMMs software, respectively. The results show that randomized Hammersley sampling sequence and medium sample size are preferred for the profile error inspection of given parts if accuracy and time are all considered. The research provides a method for free-form surface accurate inspection while minimizing the sampling time and cost.