Research on Micro/Nano Surface Flatness Evaluation Method Based on Improved Particle Swarm Optimization Algorithm - Shu, Han; Zou, Chunlong; Chen, Jianyu; Wang, Shenghuai (Frontiers in Bioengineering and Biotechnology, 2021)
Flatness error is very important to effective evaluation of surface quality. The current flatness error evaluation methods mainly evaluated the flatness of micron scale surface measured by CMM. In order to meet the needs of nanoscale micro/nano surfaces flatness error evaluation. A minimum zone method based on improved particle swarm optimization algorithm is proposed. This method combines the principle of minimum region method and hierarchical clustering method, improves the particle swarm optimization algorithm, and can evaluate the flatness error of nano scale micro/nano surface image data scanned by atomic force microscope (AFM). The influence of the area size of surface topography data on the evaluation results is also considered, and the proposed algorithm is tested and analyzed.