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贝叶斯回归的多核ESN在站立姿态下的操纵舒适性预测研究

赵川 余隋怀 寸文哲 陈晨 王龙

赵川, 余隋怀, 寸文哲, 陈晨, 王龙. 贝叶斯回归的多核ESN在站立姿态下的操纵舒适性预测研究[J]. 机械科学与技术, 2019, 38(11): 1778-1783. doi: 10.13433/j.cnki.1003-8728.20190046
引用本文: 赵川, 余隋怀, 寸文哲, 陈晨, 王龙. 贝叶斯回归的多核ESN在站立姿态下的操纵舒适性预测研究[J]. 机械科学与技术, 2019, 38(11): 1778-1783. doi: 10.13433/j.cnki.1003-8728.20190046
Zhao Chuan, Yu Suihuai, Cun Wenzhe, Chen Chen, Wang Long. Study on Multi-reservoir Echo State Network Modeling of Control Handing Comfort for Standing Posture[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(11): 1778-1783. doi: 10.13433/j.cnki.1003-8728.20190046
Citation: Zhao Chuan, Yu Suihuai, Cun Wenzhe, Chen Chen, Wang Long. Study on Multi-reservoir Echo State Network Modeling of Control Handing Comfort for Standing Posture[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(11): 1778-1783. doi: 10.13433/j.cnki.1003-8728.20190046

贝叶斯回归的多核ESN在站立姿态下的操纵舒适性预测研究

doi: 10.13433/j.cnki.1003-8728.20190046
基金项目: 

高等学校学科创新引智计划项目 B13044

工信部民机专项项目 MJ-2015-F-018

详细信息
    作者简介:

    赵川(1988-), 博士研究生, 研究方向为工业设计、人机工效, zhaochuancow@gmail.com

    通讯作者:

    余隋怀, 教授, 博士生导师, ysuihuai@vip.sina.com

  • 中图分类号: TP47

Study on Multi-reservoir Echo State Network Modeling of Control Handing Comfort for Standing Posture

  • 摘要: 操纵舒适性是人机系统研究的重要内容之一。针对操纵舒适性评价的不确定性和模糊性,构建基于贝叶斯的多核回声状态网络(Echo state network,ESN)模型,对站立姿态下的操纵舒适性进行评价。通过实验,收集不同操纵位置对用户的舒适性影响。15名被试者参与了本次实验,每个被试者需要完成100个操纵任务,实验过程中被试者的操纵姿势、目标位置、脚底压力、被试人体尺寸和主观舒适性的数据将被记录下来。选取了10%的实验数据对所提出的方法进行了验证,并与BP神经网络预测模型进行比较,结果表明T-S FNN模型具有较小的均方根误差。最后随机选取了10组操纵任务与快速上肢评估方法(RULA)进行比较,结果表明该方法和实际值相关性系数为0.97(p < 0.05),与RULA结果的相关性为0.66(p < 0.05),说明该方法能够较好地反应真实结果。
  • 图  1  操纵舒适性实验

    图  2  关节角度计算

    图  3  操纵舒适性预测MvBESN模型

    图  4  主观舒适性预测得分

    表  1  人体测量数据

    性别 年龄/y 人数/位 体重/kg 身高/cm 肩高/cm 立姿举高/cm 侧面手臂长/cm 肩部指尖长/cm 坐高/cm 坐姿下肢长/cm
    25.6±2.5 8 73.6±8.9 176.7±5.1 146.0±6.6 219.5±9.2 87.1±2.9 86.1±4.5 102.0±14.5 107.3±4.3
    24.3±3.2 7 50.9±6.7 164.6±7.4 130.9±15.8 202.9±10.6 78.6±4.9 79.4±5.7 87.9±2.4 98.6±11.0
    下载: 导出CSV

    表  2  ESN与MrBESN的预测舒适性精度比较

    模型 ESN MvBESN MvBESN MvBESN MvBESN
    储备池数量 1 50 100 150 200
    ERMS 8.51 4.83 4.26 3.87 3.95
    下载: 导出CSV

    表  3  模型评估结果

    变量 操纵1 操纵2 操纵3 操纵4 操纵5 操纵6 操纵7 操纵8 操纵9 操纵10
    目标位置 B1(2, 3) B3(3, 4) B4(1, 2) B2(3, 3) B3(1, 5) B2 (3, 3) B4(2, 2) B2(5, 1) B1(1, 4) B3(3, 4)
    舒适性实际值 32 18 16 33 13 35 16 22 26 18
    MvBESN得分 35.2 16.2 14.3 35.1 12.3 36.6 15.5 20.6 28.3 16.5
    RULA得分 5 4 5 3 6 3 5 5 3 4
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-11-30
  • 刊出日期:  2019-11-05

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