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兵工学报 ›› 2017, Vol. 38 ›› Issue (2): 233-239.doi: 10.3969/j.issn.1000-1093.2017.02.004

• 论文 • 上一篇    下一篇

面向装甲车辆乘员信息处理的作业时间预测模型研究

聂俊峰, 刘维平, 傅斌贺, 张征, 杨波   

  1. (装甲兵工程学院 机械工程系, 北京 100072)
  • 收稿日期:2016-06-15 修回日期:2016-06-15 上线日期:2017-04-01
  • 通讯作者: 刘维平(1961—), 男, 教授, 博士生导师 E-mail:lwpyxlzh@sohu.com
  • 作者简介:聂俊峰(1989—), 男, 博士研究生。 E-mail: njf0706@126.com

Predictive Operation Time Model for Information Processing Task of Crew in Armored Vehicle

NIE Jun-feng, LIU Wei-ping, FU Bin-he, ZHANG Zheng, YANG Bo   

  1. (Department of Mechanical Engineering,Academy of Armored Forces Engineering,Beijing 100072,China)
  • Received:2016-06-15 Revised:2016-06-15 Online:2017-04-01

摘要: 作业时间的准确预测是装甲车辆乘员信息处理作业状态研究的关键,对提高人机系统的作战效能具有重要意义。针对乘员作业类型向信息处理作业转变的基本趋势,以信息录入典型信息处理作业为研究对象,对其信息处理作业操作元和认知过程进行了系统分析。基于乘员操纵特性和认知特性构建了信息录入作业时间预测模型,并面向任务对预测模型进行了实验验证,旨在为解决应急任务条件下乘员信息处理作业时间预测问题探索新的途径。结果表明,该模型能够清晰地描述乘员信息录入作业的认知过程,准确地预测作业时间,具有较好的预测精度和可重用性,是一种有效可行的信息处理作业时间预测模型。

关键词: 兵器科学与技术, 装甲车辆, 信息处理, 信息录入, 时间预测模型

Abstract: The accurate prediction of operation time is essential to study the operating state of crew in armored vehicle, and is important to improve the operational effectiveness of the man-machine system. In view of a basic trend that the operation type gradually changes into information processing,the information input task is studied,and the operate-units and cognitive process are systematically analyzed. A predictive operation time model is built based on crew’s control and cognitive characteristics. The predictive operation time model is verified through experiment, with an aim to solve the prediction problem of crew’s information processing time under the condition of emergency. The test results show that the proposed model could describe the whole cognitive process of crew’s information input task and predict the reaction times of operate-units accurately. The model has high prediction accuracy and reusability.Key

Key words: ordnancescienceandtechnology, armoredvehicle, informationprocessing, informationinput, predictivetimemodel

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