虚拟维修训练中人机交互的认知负荷研究

发布时间：2018-10-16 21:32

【摘要】：随着先进科学技术的应用,各种产品技术含量日益提高,对维修人员的训练提出了更高的要求,虚拟维修训练成为了一个崭新的研究领域。本文介绍了认知负荷理论在虚拟维修训练中的重要性,并对虚拟维修训练中的认知负荷的一些特点进行了分析和研究。首先,本文介绍了虚拟维修训练的概念和研究背景,并对虚拟维修训练的国内外研究现状进行了详细的阐述。提出了本文的研究方向——虚拟维修训练中的认知负荷研究。另外,还介绍了研究中应用到的一些基本理论知识主要包括虚拟维修训练的内容,虚拟维修训练中的认知机理,认知负荷的概念,认知负荷的分类,降低认知负荷的原则,以及认知负荷的基本评估方法。其次,在有关降低认知负荷原则的基础上,通过设计对比实验验证问题完成效应和注意分散效应对虚拟维修训练中的认知负荷的影响。最后,本文研究了认知负荷各种指标在虚拟维修训练中的特点。并基于这一部分研究获得的单维度评估指标,运用人工神经网络模型中的概率神经网络和竞争型神经网络对虚拟维修训练系统中的认知负荷等级进行综合评估。对连续作业过程中不同作业时间段的认知负荷指标的变化特点进行了研究。并且运用概率神经网络对连续训练过程中的认知负荷评估指标进行预测。
[Abstract]:With the application of advanced science and technology, the technical content of various products is increasing day by day, which puts forward higher requirements for the training of maintenance personnel. Virtual maintenance training has become a new research field. This paper introduces the importance of cognitive load theory in virtual maintenance training, and analyzes and studies some characteristics of cognitive load in virtual maintenance training. Firstly, the concept and research background of virtual maintenance training are introduced, and the research status of virtual maintenance training at home and abroad is described in detail. The research direction of this paper is the research of cognitive load in virtual maintenance training. In addition, some basic theoretical knowledge applied in the research mainly includes the content of virtual maintenance training, the cognitive mechanism in virtual maintenance training, the concept of cognitive load, the classification of cognitive load, and the principle of reducing cognitive load. And the basic assessment method of cognitive load. Secondly, on the basis of the principle of reducing cognitive load, the effects of problem completion effect and attention dispersion effect on cognitive load in virtual maintenance training are verified by designing and comparing experiments. Finally, this paper studies the characteristics of cognitive load in virtual maintenance training. Based on the single dimension evaluation index obtained in this part, the cognitive load grade in the virtual maintenance training system is evaluated synthetically by using the probabilistic neural network and competitive neural network in the artificial neural network model. The change characteristics of cognitive load indexes in different working periods during continuous operation were studied. And the probabilistic neural network is used to predict the cognitive load assessment index during continuous training.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP11;TH17;TP391.9

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