Free-form surface parts quality inspection optimization with a novel sampling method

Abstract

Quality inspection is a critical step in the process of manufacturing of free-form surface parts. For dimensional quality control, registration is normally used to match the measurement model to the design model. Then, the machined errors can be visualized in the misalignment regions. Because these two models are located in different coordinate systems, an optimal spatial transformation matrix is necessary. In this area, iterative closest point (ICP) is the best known method for registration. However, the global optimum solution is intractable to compute in terms of ICP. Considering of the accuracy and efficiency of free-form surface parts quality inspection, in this paper, the maximin distance approach is introduced for model simplification with normal deviation information. Moreover, to find the optimal transformation parameters, an improved fruit fly optimization algorithm is proposed in terms of the saccade behavior of drosophila. The performance of the developed algorithms has been tested via both computer simulations and real experiments, and the results demonstrate that the proposed methods are superior to several classical approaches for free-form surface parts quality inspection.