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面向表面质量的镍基高温合金铣削参数多目标优化研究

田应权 尹瑞雪 易望远 欧丽

重庆理工大学学报2024,Vol.38Issue(3):123-131,9.
重庆理工大学学报2024,Vol.38Issue(3):123-131,9.DOI:10.3969/j.issn.1674-8425(z).2024.02.013

面向表面质量的镍基高温合金铣削参数多目标优化研究

Research on multi-objective optimization of milling parameters for nickel based high-temperature alloys facing surface quality

田应权 1尹瑞雪 1易望远 1欧丽1

作者信息

  • 1. 贵州大学 机械工程学院,贵阳 550025
  • 折叠

摘要

Abstract

A multi-objective optimization method for process parameters based on neural network and NSGA-Ⅱ algorithm is proposed to address the problem of low surface processing quality in the milling process of nickel based high-temperature alloy materials.First,different process parameters are employed for CNC milling of nickel based high-temperature alloy Inconel718 and a dataset is obtained.The surface roughness is used as the output and different process parameter combinations as the input.The sparrow search algorithm is employed to establish an SSA-BP neural network model for predicting the surface roughness of Inconel718 during milling;Subsequently,with the maximum material removal rate and minimum surface roughness as optimization objectives,a multi-objective optimization main model for NSGA Ⅱ process parameters is built.The constructed prediction network model is called the objective function of the main model and optimized to obtain the Pareto optimal solution set.TOPSIS method is employed to make optimal solution decisions on the Pareto optimal solution set and obtain the optimal combination of process parameters.Our optimization results indicate this method can be used for predicting surface roughness in CNC milling of high-temperature alloy materials and optimizing process parameters,further improving the processing quality and efficiency of CNC milling materials.

关键词

数控铣削/表面粗糙度/质量优化/难加工金属材料/神经网络

Key words

CNC milling/surface roughness/quality optimization/difficult to machine metal materials/neural network

分类

机械制造

引用本文复制引用

田应权,尹瑞雪,易望远,欧丽..面向表面质量的镍基高温合金铣削参数多目标优化研究[J].重庆理工大学学报,2024,38(3):123-131,9.

基金项目

国家自然科学基金项目(51765010) (51765010)

重庆理工大学学报

OA北大核心

1674-8425

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