薄板类零件加工精度可靠性分析及工艺参数优化

doi:10.3969/j.issn.1004-132X.2022.11.002

摘要/Abstract

摘要： 针对薄板类零件加工过程中加工变形导致加工精度低的问题，利用有限元法和高斯过程回归算法建立了加工变形预测模型，综合考虑机床运动误差与工件加工变形,对薄板件加工精度可靠性进行分析，建立了以加工效率和平均加工变形为目标、加工精度可靠度为约束的铣削加工工艺参数优化设计模型，并利用多目标优化算法进行求解，确定了协调加工效率和加工变形最优的工艺参数组合。案例研究结果表明，经优化设计后最低加工精度可靠度达到98.21%，平均加工变形减小21.14%，加工效率提高了4.18%，为薄板类零件铣削加工工艺参数选择提供了一种可行的方法。

关键词: 薄板类零件, 加工精度, 可靠性分析, 工艺参数优化

Abstract: To address the problems of low machining accuracy caused by cutting deformations during the machining processes of the thin-plate parts, a machining deformation prediction model was established by using the finite element method and Gaussian process regression algorithm. Then, the workpiece processing deformations and machine tool motion errors were considered comprehensively to analyze the reliability of the thin-plate machining accuracy. A milling process parameter optimization design model was established with machining efficiency and average machining deformation as the goal, and the machining accuracy reliability as the constraint. The multi-objective optimization algorithm was used to solve the model, determining the optimal combination of processing parameters for coordinated processing efficiency and processing deformations. The case study indicates that after the optimized design, the minimum machining accuracy reliability reaches 98.21%, the average machining deformations are reduced by 21.14%, and the machining efficiency is increased by 4.18%. A feasible method is provided for the selection of milling process parameters for thin plate parts.

Key words: thin-plate part, machining accuracy, reliability analysis, processing parameter optimization

中图分类号:

TH161

易茜, 李聪波, 潘建, 张友. 薄板类零件加工精度可靠性分析及工艺参数优化[J]. 中国机械工程, 2022, 33(11): 1269-1277.

YI Qian, LI Congbo, PAN Jian, ZHANG You. Reliability Analysis of Machining Accuracy and Processing Parameter Optimization for Thin-plate Parts[J]. China Mechanical Engineering, 2022, 33(11): 1269-1277.

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链接本文: http://www.cmemo.org.cn/CN/10.3969/j.issn.1004-132X.2022.11.002

http://www.cmemo.org.cn/CN/Y2022/V33/I11/1269

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