采用多元非线性回归模型的无头铆钉安装干涉量预测

李晓锋; 常正平; 高雅芝; 霍永兴; 宋建生; 王仲奇

doi:10.7652/xjtuxb202401015

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采用多元非线性回归模型的无头铆钉安装干涉量预测

更新时间：2025-05-13

- 采用多元非线性回归模型的无头铆钉安装干涉量预测
- Predicting Interference of Headless Rivet Using Multiple Nonlinear Regression
- 西安交通大学学报 2024年58卷第1期页码：157-166
- 作者机构：
  
  1. 西北工业大学机电学院,西安,710072
  2. 中航西安飞机工业集团股份有限公司,西安,710089
- 作者简介：
  
  : 2023-05-04。作者简介: 李晓锋(1999—),男,硕士生
  常正平(通信作者),男,副研究员,硕士生导师。基金项目: 国家自然科学基金资助项目(51905443)
- 基金信息：
  
  : 2023-05-04。作者简介: 李晓锋(1999—),男,硕士生;常正平(通信作者),男,副研究员,硕士生导师。基金项目: 国家自然科学基金资助项目(51905443);航空科学基金资助项目(ASFC-201916053001)。
- DOI：10.7652/xjtuxb202401015
  中图分类号： V262.4
- 网络首发：2024-01-10，
  
  纸质出版：2024
- 稿件说明：
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李晓锋, 常正平, 高雅芝, 等. 采用多元非线性回归模型的无头铆钉安装干涉量预测[J]. 西安交通大学学报, 2024,58(1):157-166.

LI Xiaofeng, CHANG Zhengping, GAO Yazhi, et al. Predicting Interference of Headless Rivet Using Multiple Nonlinear Regression[J]. 2024, 58(1): 157-166.
李晓锋, 常正平, 高雅芝, 等. 采用多元非线性回归模型的无头铆钉安装干涉量预测[J]. 西安交通大学学报, 2024,58(1):157-166. DOI： 10.7652/xjtuxb202401015.

LI Xiaofeng, CHANG Zhengping, GAO Yazhi, et al. Predicting Interference of Headless Rivet Using Multiple Nonlinear Regression[J]. 2024, 58(1): 157-166. DOI： 10.7652/xjtuxb202401015.

摘要

为明晰被连接件材料性能对安装干涉量的影响规律

并进一步为新材料扩展应用提供可靠性预测

在铆接过程有限元仿真数据基础上

提出了一种采用多元非线性回归模型的无头铆钉安装干涉量预测方法。首先

根据实际铆接过程建立有限元仿真模型

通过铆接试验验证模型有效性。然后

采用有限元和正交试验法

研究了被连接件弹性模量、屈服强度、强化系数和应变强度指数及其交互作用对铆接干涉量水平的显著性

明确了各因素对安装干涉量的影响效果。最后

选用幂函数作为多元非线性回归的函数形式

剔除显著性较低因素项

建立了待测位置干涉量回归预测模型。结果表明

在一定铆接工艺条件下

屈服强度和应变强度指数及其交互作用是影响干涉量水平的主要因素。对比模拟值与回归模型预测值发现两者变化趋势一致

且误差不超过10%

表明干涉量多元回归预测模型具有有效性。

Abstract

This study proposes a method for predicting the installation interference of headless rivet using a multiple nonlinear regression model based on the finite element simulation data of the riveting process

with the aim to elucidate the influence of material properties on the interference during installation and to provide reliable predictions for the use of new materials. Firstly

a finite element simulation model is established based on the actual riveting process and its validity is verified through riveting experiments. Subsequently

finite element analysis and orthogonal testing techniques are employed to examine the significance of various factors

such as elastic modulus

yield strength

strengthening coefficient

and strain strength index

along with their interactions on installation interference

determining the influence of each factor on the riveting interference. Finally

the multiple nonlinear regression model is formulated using a power function

and less significant factors are eliminated. The results show that

under specific riveting process conditions

yield strength and strain strength index

as well as their interaction

are the primary factors affecting the interference. By comparing the simulated values and the predicted values of the regression model

it is observed that the two values exhibit consistent variation trends

with errors remaining below 10%

demonstrating the effectiveness of the multiple regression models in predicting riveting interference.

关键词

Keywords

references

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