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应用变量优选的PLSR分析直线进给轴热扭曲行为

吴倩倩 林献坤

吴倩倩, 林献坤. 应用变量优选的PLSR分析直线进给轴热扭曲行为[J]. 机械科学与技术, 2019, 38(1): 90-95. doi: 10.13433/j.cnki.1003-8728.20180106
引用本文: 吴倩倩, 林献坤. 应用变量优选的PLSR分析直线进给轴热扭曲行为[J]. 机械科学与技术, 2019, 38(1): 90-95. doi: 10.13433/j.cnki.1003-8728.20180106
Wu Qianqian, Lin Xiankun. Exploiting PLSR with Variable Optimization Selection in Thermal Distortion Behavior Analysis of Linear Feed Drive Axis[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(1): 90-95. doi: 10.13433/j.cnki.1003-8728.20180106
Citation: Wu Qianqian, Lin Xiankun. Exploiting PLSR with Variable Optimization Selection in Thermal Distortion Behavior Analysis of Linear Feed Drive Axis[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(1): 90-95. doi: 10.13433/j.cnki.1003-8728.20180106

应用变量优选的PLSR分析直线进给轴热扭曲行为

doi: 10.13433/j.cnki.1003-8728.20180106
基金项目: 

上海高校青年教师培养计划项目 ZZGCD15127

详细信息
    作者简介:

    吴倩倩(1986-), 讲师, 硕士研究生, 研究方向为数控装备设计与优化, wuqianqian1186@sina.com

  • 中图分类号: TP391

Exploiting PLSR with Variable Optimization Selection in Thermal Distortion Behavior Analysis of Linear Feed Drive Axis

  • 摘要: 为了探索直线电机驱动的高速直线进给轴热扭曲变形的影响因素,在试验的基础上,给出应用向前变量智能自筛选的偏最小二乘线性回归模型(Partial least squares regression,PLSR)分析影响进给轴热扭曲行为关联因素的分析方法。通过在自构建的进给轴试验平台,建立进给轴扭曲变形的测试系统,给出直线进给轴在发热过程和强冷却作用过程的热扭曲变形采样与进给轴温度动态采集方案。应用周期大变异的遗传算法为偏最小二乘回归参数的自检验方法,给出分析方法的具体实现步骤。通过实验和回归识别计算,分析了进给轴的温度分布及其对热扭曲行为的影响规律。结果表明,给出的变量自筛选偏最小二乘线性回归分析方法,可有效的筛选复相关的温度测点变量,并保持较高的回归识别精度,给出的方法与全变量PLSR和向后变量筛选的Bootstrap方法进行了比较,进一步表明了给出的回归分析方法的优越性。
  • 图  1  优选变量的染色体编码方式

    图  2  试验平台及传感器布置

    图  3  进给轴相关布置点的温升情况

    图  4  进给轴位置扭曲情况

    图  5  GA-PLSR识别效果

    图  6  各测点温度对扭曲变形回归的影响

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出版历程
  • 收稿日期:  2017-11-20
  • 刊出日期:  2019-01-05

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