Design of a Femtosecond Laser Percussion Drilling Process for Ni-Based Superalloys Based on Machine Learning and the Genetic Algorithm

• DOI: 10.3390/mi14112110
• Publication Date: 2023-11-17T14:23:43Z
• Authors: Zhixi Zhao; Yunhe Yu; Ruijia Sun; Wanrong Zhao; Hao Guo; Zhen Zhang; Chenchong Wang
• Keywords: Drilling engineering; Laser drilling; Percussion

Femtosecond laser drilling is extensively used to create film-cooling holes in aero-engine turbine blade processing. Investigating and exploring the impact of processing parameters on achieving high-quality crucial. The traditional trial-and-error approach, which relies experiments, time-consuming has limited optimization capabilities for holes. To address this issue, paper proposes a process design method using machine learning genetic algorithm. A dataset percussion femtosecond was primarily established train models. An optimal building prediction model determined by comparing analyzing different algorithms. Subsequently, Gaussian support vector regression algorithm were combined optimize taper material removal rate within outside original data ranges. Ultimately, comprehensive quality efficiency achieved relative data. proposed framework study offers highly efficient cost-effective solution optimizing process.