• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2022, Vol. 58 ›› Issue (10): 383-394.doi: 10.3901/JME.2022.10.383

• 交叉与前沿 • 上一篇    

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基于理想压力的机车座椅优化设计与舒适度试验研究

范沁红1, 江星辰1, 武学良2, 聂敏2, 辛运胜1, 李浩林1, 贾显淯1   

  1. 1. 太原科技大学机械工程学院 太原 030024;
    2. 中车大同电力机车有限公司 大同 037038
  • 收稿日期:2021-12-17 修回日期:2022-02-07 出版日期:2022-05-20 发布日期:2022-07-07
  • 通讯作者: 江星辰(通信作者),男,1997年出生,硕士研究生。主要研究方向为车辆人机工程。E-mail:1551249641@qq.com
  • 作者简介:范沁红,女,1976年出生,博士,副教授。主要研究方向为工程机械与车辆人机工程。E-mail:tyustfqh@163.com
  • 基金资助:
    山西省科技平台(201805D121006)、山西省"1331工程"重点学科建设计划经费和山西省科技重大专项(20181102002)资助项目。

Experimental Research on Optimization Design and Comfort of Locomotive Seat Based on Ideal Pressure

FAN Qinhong1, JIANG Xingchen1, WU Xueliang2, NIE Min2, XIN Yunsheng1, LI Haolin1, JIA Xianyu1   

  1. 1. School of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024;
    2. CRRC Datong Co., Ltd., Datong 037038
  • Received:2021-12-17 Revised:2022-02-07 Online:2022-05-20 Published:2022-07-07

摘要: 为了提高某出口型电力机车司机座椅舒适性,结合人机工程仿真软件JACK、主观感知舒适度量表及压力坐垫对司机座椅人机系统进行分析,进而基于人体工程学的座椅靠背设计方法对座椅靠背形态进行优化,对优化后座椅靠背的人机匹配度进行了仿真分析和主客观试验验证,结果表明优化后的靠背设计方案比靠背原型的人机交互匹配度更高,且能对司机背部形成良好的支撑。最后利用Matlab LIBSVM工具箱建立舒适度预测模型对座椅舒适度进行预测分析,得到均方误差MSE=0.0037534、相关系数R=93.0631%,该模型预测精度高,可大幅简化主观评价流程。该座椅靠背设计方法可为轨道交通装备司机座椅的舒适性设计提供理论参考和试验依据。

关键词: 理想压力, 电力机车, 司机座椅, 优化设计, 舒适度

Abstract: In order to improve the comfort of the driver's seat of an export-oriented electric locomotive, the man-machine system of the driver’s seat was analyzed by combining human-computer engineering simulation software JACK, subjective perceived comfort scale and pressure cushion, and then the form of the seat back was optimized based on ergonomic design method. The human-machine matching degree of the optimized backrest is simulated and verified by subjective and objective experiments. The results show that the optimized backrest design scheme has higher human-machine interaction matching degree than the prototype back, and can form a good support for the driver's back. Finally, a comfort prediction model was established by using MATLAB LIBSVM toolbox to predict and analyze seat comfort, and the mean square error (MSE) and correlation coefficient (R) were obtained as 0.003 753 4 and 93.063 1%, respectively. The prediction accuracy of this model was high and the subjective evaluation process could be greatly simplified. This method can provide theoretical reference and experimental basis for the comfort design of rail transit equipment driver’s seat.

Key words: ideal pressure, electric locomotive, driver seat, optimization design, comfort

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