• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2022, Vol. 58 ›› Issue (1): 221-230.doi: 10.3901/JME.2022.01.221

• 数字化设计与制造 • 上一篇    下一篇

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考虑粗糙表面特性的驱动轴系统轴向派生力的区间不确定性优化

冯华渊, 上官文斌, 康英姿   

  1. 华南理工大学机械与汽车工程学院 广州 510641
  • 收稿日期:2021-01-04 修回日期:2021-04-08 出版日期:2022-01-05 发布日期:2022-03-19
  • 通讯作者: 康英姿(通信作者),女,1970年出生,博士,副教授,主要研究方向为汽车零部件的设计理论与方法、汽车动力学分析、通风与空调系统的节能优化。E-mail:yzkang@scut.edu.cn
  • 作者简介:冯华渊,男,1993年出生,博士研究生。主要研究方向为驱动轴系统的动力学、接触摩擦和不确定性。E-mail:2728455611@qq.com
  • 基金资助:
    国家自然科学基金(11472107)和广东省自然科学基金(2019A1515011612)资助项目。

Interval Optimization for Generated Axial Force of Drive Shaft Systems Considering Rough Surface Characteristics

FENG Huayuan, SHANGGUAN Wenbin, KANG Yingzi   

  1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510641
  • Received:2021-01-04 Revised:2021-04-08 Online:2022-01-05 Published:2022-03-19

摘要: 以一驱动轴系统为研究对象,基于分形理论,首先建立了一种考虑粗糙表面特性的轴向派生力的确定性模型。通过轴向派生力测试,验证了确定性模型的有效性。在考虑粗糙表面特性后,轴向派生力具有较大的不确定性。为了更有效地分析和优化轴向派生力,基于建立的确定性模型和勒让德多项式,提出了一种轴向派生力的区间不确定性模型。在区间模型中,输入参数被视为区间变量。以区间模型的上界和不确定度为优化目标,提出了轴向派生力的多目标区间不确定性优化方法。为了提高优化效率,结合勒让德多项式特点和顶点法,提出了一种快速获取区间模型上界和不确定度的方法。数值算例表明:基于提出的优化方法,不仅可使轴向派生力的上界满足设计要求,还可提高轴向派生力的鲁棒性。

关键词: 驱动轴系统, 轴向派生力, 分形理论, 区间不确定性, 多目标区间优化

Abstract: Taking a drive shaft system as the research object, a deterministic model of the generated axial force (GAF) considering rough surface characteristics (RSC) is established based on fractal theory. By measuring the GAF of a drive shaft system, the proposed deterministic model of the GAF is verified. Since there are many factors effecting the GAF after considering RSC, the GAF has greater uncertainty. To study the GAF more effectively, an interval model for the GAF is proposed based on Legendre polynomials and the deterministic model. In the interval model, the influencing factors are considered as interval parameters. Taken the upper bound and the uncertainty level of the GAF as the optimization objectives, a multi-objective interval optimization method for the GAF is proposed. In order to enhance the optimization efficiency, an efficient method for calculating the upper bound and the uncertainty level of the GAF is proposed by combining Legendre polynomials and vertex method. The results of the numerical examples show that through the multi-objective interval optimization, not only the upper bound of the GAF can meet the design requirement, but also the robustness of the GAF is enhanced.

Key words: drive shaft systems, generated axial force, fractal theory, interval uncertainty, multi-objective optimization

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