姜一豪, 郭悦, 孙兆泽, 李晓月. 基于贝叶斯网络的加工变形不确定性分析及度量[J]. 制造技术与机床, 2024, (10): 130-138. DOI: 10.19287/j.mtmt.1005-2402.2024.10.018
引用本文: 姜一豪, 郭悦, 孙兆泽, 李晓月. 基于贝叶斯网络的加工变形不确定性分析及度量[J]. 制造技术与机床, 2024, (10): 130-138. DOI: 10.19287/j.mtmt.1005-2402.2024.10.018
JIANG Yihao, GUO Yue, SUN Zhaoze, LI Xiaoyue. Uncertainty analysis and measurement of machining distortion based on Bayesian network[J]. Manufacturing Technology & Machine Tool, 2024, (10): 130-138. DOI: 10.19287/j.mtmt.1005-2402.2024.10.018
Citation: JIANG Yihao, GUO Yue, SUN Zhaoze, LI Xiaoyue. Uncertainty analysis and measurement of machining distortion based on Bayesian network[J]. Manufacturing Technology & Machine Tool, 2024, (10): 130-138. DOI: 10.19287/j.mtmt.1005-2402.2024.10.018

基于贝叶斯网络的加工变形不确定性分析及度量

Uncertainty analysis and measurement of machining distortion based on Bayesian network

  • 摘要: 大型零件由刚性的毛坯加工成薄壁、弱刚性的复杂结构零件,几何结构特征不断变化,结构动态特性、初始残余应力分布以及表面层状态亦随之不断变化,因此薄壁件的加工过程充斥着诸多不确定性。围绕“应力—变形”力学关系,从应力状态不确定性的角度出发,系统分析残余应力的不确定性对加工变形的影响。采用矩估计与自回归模型联合评估方法或者最小二乘拟合外推与自回归模型联合评估方法评估初始残余应力和表面残余应力的不确定度。构造加工变形的贝叶斯网络模型,开展加工变形不确定性的推理过程,采用后验概率指标量化输入因素的不确定性对加工变形的影响。结果表明,初始残余应力和表面残余应力的不确定性分别使加工变形增大17.8%和1.0%~6.4%。

     

    Abstract: During the machining process of large components from rigid blanks into thin-wall and weakly rigid complex structural parts, geometrical structure characteristics, dynamic structure properties and initial residual stress distribution as well as the state of the surface layer are constantly changing, so the machining of thin-wall parts is full of many uncertainties. Based on the stress-strain mechanical relationship, the influence of residual stress uncertainty on machining distortion is systematically analyzed from the view of stress state uncertainty. The uncertainty of initial residual stress and surface residual stress was evaluated by the joint evaluation method of moment estimation and autoregressive model or the joint evaluation method of least square fitting extrapolation and autoregressive model. The Bayesian network model of machining distortion is constructed, the inference process of machining distortion uncertainty is carried out, and the influence of uncertainty of input factors on machining distortion is quantified by a posterior probability. The results show that the uncertainties of initial residual stress and surface residual stress increase the machining distortion by 17.8% and 1.0%-6.4%, respectively.

     

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