基于工艺参数优化的高温合金加工技术研究

Research on Superalloy Processing Technology Based on Process Parameter Optimization

摘要: 高温合金因其优异的力学性能和耐高温特性，广泛应用于航空航天、能源动力等关键领域。然而，其固有的难加工特性严重制约了加工效率与经济效益的提升。为实现高温合金的高效高质加工，本文开展基于智能算法的工艺参数优化研究。首先，引入并采用萤火虫算法这一新兴的元启发式优化方法，以表面粗糙度最小化和材料去除率最大化为优化目标，构建幂函数形式的表面粗糙度预测模型，建立了工艺参数多目标优化模型。最后，设计GH4169侧铣工程应用案例，对比传统经验参数与优化参数的加工效果。结果表明，优化后参数在满足表面粗糙度 ≤ 1.5 μm工艺要求的前提下，材料去除率提升125%，表面粗糙度降低30.9%，实现了加工效率与表面质量的协同提升。本研究将智能算法与工程实践紧密结合，形成了一条从“理论建模”到“参数优化”再到“工程验证”的完整技术路径。研究成果为攻克高温合金高效精密加工难题提供了具有实用价值的参考，并证实了智能优化算法在复杂制造工艺参数决策中的巨大潜力。

Abstract: Because of its excellent mechanical properties and high temperature resistance, superalloys are widely used in key fields such as aerospace, energy and power. However, its inherent difficult-to-machine characteristics seriously restrict the improvement of processing efficiency and economic benefits. In order to achieve high-efficiency and high-quality processing of superalloys, this paper carried out research on process parameter optimization based on intelligent algorithms. Firstly, the firefly algorithm, an emerging meta-heuristic optimization method, is introduced and adopted. The surface roughness prediction model in the form of power function is constructed with the minimization of surface roughness and the maximization of material removal rate as the optimization objectives, and the multi-objective optimization model of process parameters is established. Finally, the engineering application case of GH4169 side milling is designed, and the processing effect of traditional empirical parameters and optimized parameters is compared. The results show that the optimized parameters increase the material removal rate by 125 % and reduce the surface roughness by 30.9% on the premise of meeting the process requirements of surface roughness ≤ 1.5 μm. The synergistic improvement of processing efficiency and surface quality is realized. This study closely combines intelligent algorithms with engineering practice, forming a complete technical path from “theoretical modeling” to “parameter optimization” to “engineering verification”. The research results provide a practical reference for solving the problem of high efficiency and precision machining of superalloys, and confirm the great potential of intelligent optimization algorithms in the decision-making of complex manufacturing process parameters.