Response Surface Method for Complex Mechanical Assembly

doi:10.7652/xjtuxb201809004

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Response Surface Method for Complex Mechanical Assembly

更新时间：2025-05-01

- Response Surface Method for Complex Mechanical Assembly
- Vol. 52, Issue 9, Pages: 28-36(2018)
- 作者机构：
  
  西北工业大学机电学院,西安,710072
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201809004
  CLC： TH132.46
- Online First：10 September 2018，
  
  Published：2018
- 稿件说明：
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Response Surface Method for Complex Mechanical Assembly[J]. 2018, 52(9): 28-36.
DOI：

Response Surface Method for Complex Mechanical Assembly[J]. 2018, 52(9): 28-36. DOI： 10.7652/xjtuxb201809004.

摘要

针对复杂机械装配体优化过程中的隐性目标函数问题

提出了基于统计学理论的响应面优化设计方法

并以齿轮驱动涡扇发动机(GTF)减速器结构系统的优化设计为案例

详细阐述了该方法的主要思想与基本过程。使用Python语言在Abaqus平台上开发了该系统参数化的有限元分析(FEA)程序

以自动实现前、后处理及求解等全过程; 采用两水平全因子正交试验设计方法对主要的结构参数进行析因设计

确定了参与优化的设计变量; 采用优化的拉丁超立方抽样方法并调用参数化的FEA程序

求得了对应结构系统上的最大von Mises等效应力

并以该应力为目标函数建立了响应面优化模型。优化后的系统满足强度条件

且整体刚度较优化前提高了7.13%

最大von Mises等效应力和最大接触应力分别降低了12.15%和18.99%

有效提高了该结构系统的工作性能。将数值最优解反代入有限元模型中再次建模求解

所得结果验证了该响应面模型的正确性。案例分析及验证结果表明

本文方法在工程应用方面具有一定的普适性及优越性

能为更多的隐性优化问题提供设计参考及解决方案。

Abstract

Aiming at the problem of implicit objective function in the optimization of complex mechanical assembly

a design method with response surface optimization is proposed based on statistical theory. Taking the optimization design of the structure system in geared turbofan engine(GTF)reducer as the example

the main idea and basic process of the proposed method are explained in detail. A parametric program in Python language is developed on Abaqus platform for the automatic finite element analysis(FEA)of the system. Then the factorial design is conducted for the main structural parameters using two-level orthogonal test design method to determine the design variables. Invoking the developed FEA program

the maximum von Mises stress is obtained by the optimized Latin hypercube sampling method

and the response surface optimization model is established for the Mises function accordingly. The obtained optimal structure system meets the strength requirements. The stiffness is increased by 7.13%

while the von Mises stress and the contact stress are decreased by 12.15% and 18.99%

respectively. The response surface model is validated by the additional FEA results under the optimal geometric parameters. The case analysis and verification results indicate better applicability and superiority of the proposed method in engineering application. This study may provide design reference and solution to other implicit optimization problems.

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Keywords

references

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