This invention relates to a method for optimizing ultrafast
laser micromachining parameters based on causal enhancement modeling, comprising the following steps: S1, constructing a multi-dimensional dataset for ultrafast
laser micromachining and performing hierarchical filtering; S2, mining the dynamic causal relationship between
processing parameters and quality indicators and quantifying the causal effect; S3, constructing a dynamic causal enhancement-based micromachining quality prediction
surrogate model; S4, establishing a multi-objective
particle swarm optimization algorithm with quality priority to optimize
processing parameters; S5, experimental
verification and iterative parameter optimization. The method provided by this invention achieves intelligent, efficient, and precise optimization of
laser processing parameters by constructing a
surrogate model with dynamic causal
feature fusion and combining it with a multi-objective
particle swarm optimization algorithm with quality priority, thereby improving the consistency and stability of micro-hole processing quality.