计算机集成制造系统 ›› 2024, Vol. 30 ›› Issue (5): 1683-1693.DOI: 10.13196/j.cims.2023.0209

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面向任务的载人深潜人机交互信息重要度评估

王卉1,余隋怀1,陈登凯1+,张伟2,陈晨1   

  1. 1.西北工业大学工业设计与人机工效工信部重点实验室
    2.中国船舶科学研究中心
  • 出版日期:2024-05-31 发布日期:2024-06-12
  • 作者简介:王卉(1991-),女,山西临汾人,博士研究生,研究方向:人机工效、人机交互、工业设计等,E-mail:wanghui0617@mail.nwpu.edu.cn; 余隋怀(1962-),男,吉林通化人,教授,博士,博士生导师,研究方向:人机工效、计算机辅助工业设计等,E-mail:ysuihuai@vip.sina.com; +陈登凯(1973-),男,陕西榆林人,教授,博士,博士生导师,研究方向:工业设计、人因工程、智能制造等,通讯作者,E-mail:chendengkai@nwpu.edu.cn; 张伟(1988-),男,安徽寿县人,高级工程师,硕士,研究方向:深海潜水器电气控制,E-mail:515573226@qq.com; 陈晨(1992-),女,陕西富平人,博士研究生,研究方向:产品协同设计、计算机辅助工业设计,E-mail:18391609257@163.com。
  • 通讯作者简介:陈登凯(1973-),男,陕西榆林人,教授,博士,博士生导师,研究方向:工业设计、人因工程、智能制造等,通讯作者,E-mail:chendengkai@nwpu.edu.cn
  • 基金资助:
    国家重点研发计划资助项目(2016YFC0300600)。

Mission-oriented human-machine interaction information importance assessment of deep-sea manned submersible

WANG Hui1,YU Suihuai1,CHEN Dengkai1+,ZHANG Wei2,CHEN Chen1   

  1. 1.Key Laboratory of Industrial Design and Ergonomics,Ministry of Industry and Information Technology,Northwestern Polytechnical University
    2.China Ship Research Center
  • Online:2024-05-31 Published:2024-06-12
  • Supported by:
    Project supported by the National Key R&D  Program,China(No.2016YFC0300600).

摘要: 为更好地识别复杂任务环境下深海载人潜水器驾驶舱人机交互信息重要度差异,提出一种基于复杂网络的人机交互信息重要度评估方法。以悬停采样任务为研究对象,运用决策阶梯模型及任务-网络建模技术识别复杂任务相关人机交互信息元及逻辑关联,构建交互信息复杂网络模型。基于网络拓扑特征参数,从节点间逻辑影响关系的角度提出节点全局及局部影响效应评估指标,结合解释结构模型层级权重指标对交互信息节点重要度综合值进行计算,得出悬停采样任务人机交互信息重要度排序。将排序结果与其他4种算法进行对比,在证明计算有效的基础上,邀请潜航员结合实际任务流程对交互信息进行主观重要度评估。结果显示,研究所得重要度排序结果与潜航员主观排序结果呈强相关,且对重要交互信息元的识别结果与潜航员主观感知相符合,验证了所提方法识别复杂任务人机交互信息重要度差异的有效性。

关键词: 载人潜水器, 人机交互, 信息重要性, 复杂网络, 解释结构模型

Abstract: To identify the differences of the importance of human-machine interaction information in the cockpit of deep-sea manned submersible during complex mission,a complex network-based human-machine interaction information importance assessment method was proposed.Taking the hover sampling task as the research object,the decision ladder model and task network modeling techniques were applied to identify the human-machine interaction information elements and logical associations related to the complex task,and a complex network model of the interaction information was constructed.Based on the network topology feature parameters,the node global and local influence effect assessment indexes were proposed from the perspective of the logical influence relationship between nodes,and the integrated value of interaction information node importance was calculated by combining the interpretive structural model hierarchical weight indexes to derive the hover sampling task human-computer interaction information importance ranking.The ranking results were compared with the other four algorithms,and the submariners were invited to evaluate the subjective importance of the interaction information in the context of the actual mission process based on the proof that the calculation was valid.The results showed that the importance ranking results obtained from the study were strongly correlated with the subjective ranking results of the submariners,and the identification of important interaction information elements was consistent with the subjective perception of the submariners,which validated the effectiveness of the proposed method to identify the differences of the importance of human-machine interaction information for complex tasks.

Key words: manned submersible, human machine interaction, information importance, complex network, interpretive structural modeling

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