A two-module automated scanning inspection planning methodology for complex surfaces on coordinate measuring machine. (October 2022) - Yan, Yichen; He, Gaiyun; Sang, Yicun; Yao, Chenglin; Wang, Sitong; Chen, Faze
Graphical abstract: Highlights: A Cobweb-Like adaptive Sampling strategy (CLS) and an inspection path planner are proposed. An Improved Ant Colony Optimization (IACO) to solve the Must-pass Clustered TSP (MCTSP). A better capability to capture large form errors on the irregular error distributions. Efficient inspection paths reduce the unnecessary transition distances by 31%-75%. Abstract: Coordinate measuring machine (CMM) plays an essential role in the high precision measurement of complex surfaces. With the emergence of the continuous-contact scanning probe, it becomes possible to inspect large-scale scanning lines rapidly without losing accuracy. Focusing on scanning line distribution and inspection path planning, this paper proposes a two-module scanning inspection planning methodology. Firstly, a Cobweb-Like adaptive Sampling strategy (CLS) is designed to sample form errors by distributing scanning lines in a cobweb-shape mode. Secondly, an inspection path planner is utilized to plan local and global inspection paths. An Improved Ant Colony Optimization (IACO) is proposed to generate time-saving paths for discrete scanning lines. The CLS simulations and scanning experiments are conducted. The methodology can capture large form errors with the minimum inspection cost. Unnecessary transition distances are reduced by 31%-75%. This work enhances the inspection capability of the scanning probe on CMM.