切削参数的两阶段优化系统

以汽车轴承支架轴承孔的精镗切削为例，综合运用田口方法、灰色关联度分析、倒传递神经网络和粒子群算法等相关技术，对切削参数进行两阶段优化，迅速有效地找出最佳切削参数组合，不仅保证加工精度符合多目标要求，而且提升产品的稳定性。通过分析和验证表明，该方法实用有效，为提高机械加工企业的市场竞争力开辟了一种新的思路和途径。

A Two-stage Optimization System for Cutting Parameters

Based on the fine boring of the bearing holes of the auto bearing support, Taguchi experiments, grey relational analysis, the back propagation neural network and particle swarm optimization are employed to optimize the cutting parameters. The two stage optimization system can rapidly obtain the best cutting parameter settings to improve the quality of components and the stability of processing. The result demonstrates the feasibility and effectiveness of the proposed approach. It provides a novel approach and pathway for mechanical processing enterprises to enhance their competitiveness.