中国机械工程

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[装配技术]基于偏最小二乘回归的运动机构装配质量关键控制点判定方法

鞠萍华;陈资;冉琰;肖兵   

  1. 重庆大学机械传动国家重点实验室,重庆,400044
  • 出版日期:2020-07-10 发布日期:2020-08-03
  • 基金资助:
    国家自然科学基金资助项目(51705048,51575070);
    国家科技重大专项(2016ZX04004-005)

Key Assembly Quality Control Point Judgment Method in Motion Mechanisms Based on PLSR

JU Pinghua;CHEN Zi;RAN Yan;XIAO Bing   

  1. The State Key Laboratory of Mechanical Transmission,Chongqing University,Chongqing,400044
  • Online:2020-07-10 Published:2020-08-03

摘要: 为提高复杂运动机构装配质量,提出了一种基于偏最小二乘回归(PLSR)的运动机构装配质量关键控制点判定方法。基于“功能—运动—动作”的结构化分解方法,定义了元动作和元动作链的概念;将元动作链中最后一个元动作输出运动参数作为装配质量的分析对象,以状态空间模型和分层迭代法为工具构建元动作链动力传递模型,建立装配质量分析对象与各级元动作内部影响因素之间的联系;利用PLSR解决各级元动作内部影响因素之间的多重共线性和样本数据过少的问题,并且以变量投影重要性指标衡量影响因素重要程度。最后,以砂轮架X轴进给运动下的元动作链为例,证明了该方法能有效地提取出与装配质量最密切的影响因素。

关键词: 装配, 质量控制点;偏最小二乘回归;功能结构化分解;元动作链

Abstract: To enhance the assembly quality of complex motion mechanisms, a key assembly quality control point judgment method in motion mechanisms was proposed based on PLSR. Firstly, the definitions of meta-action and meta-action chain were introduced based on “function—motion— action” functional structural decomposition. Secondly, the kinematics parameters of the terminal meta-action in meta-action chain were taken as the assembly quality analysis object,the power-transmitting model for meta-action chain was developed based on the state space model and the hierarchical iteration method, which reflected the relationship between the assembly quality analysis object and the influential factors in meta-action. Thirdly, the PLSR was used to solve the multicollinearity problems and few sample data problems of the influential factors, and the variable importance projection index was utilized to measure the importance degree of each influencial factor. Finally, the meta-action chain under the X-axis feed motion of grinder carriage was taken as an example, the results prove that the method may effectively figure out the most influential factors related to assembly quality.

Key words: assembly, quality control point; partial least squares regression(PLSR); functional structural decomposition; meta-action chain

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