智能控制系统的引入虽然提升了工业系统现场设备的安全性，但同时也增加了控制室中作业人员对于情景意识能力的需求。随着界面的信息量剧增，作业难度增加等因素的产生，加速了控制室作业人员的疲劳产生，个人的情景意识水平也因此受到影响，从而使作业人员面对突发事件的感知、理解等能力逐渐下降，最终造成人因失误。目前VDT疲劳作为控制室中影响情景意识的主要因素，相关的研究较少，尤其对于煤矿，电站等相关行业控制室。基于此，本文使用脑电、眼动等多模态数据探讨控制室中VDT疲劳对作业人员情景意识的影响机制，并根据所获得的主客观数据建立情景意识的评估模型，最后基于研究结果对控制室的VDT作业提出相关建议。

本文采用E-Prime软件呈现情景意识实验材料，选取19名控制室的作业人员作为被试，在作业人员岗位作业前后分别进行情景意识测度实验，结合脑电、眼动等生理仪器采集相关数据。对作业人员的情景意识相关数据进行预处理，随后采用SPSS软件对每一段数据进行统计学分析，基于数据的显著性和相关性选取最优指标作为模型的输入端，输出端选取客观数据，构建多模态数据融合的情景意识评估模型。研究结果表明：主观客观数据出现了显著变化，可以推断被试已经产生VDT疲劳，结合主观数据及脑电数据可以发现控制室中作业人员感受到的疲劳主要是以脑力负荷和视觉负荷累积所导致的主动疲劳，并且这种主动疲劳会通过影响作业人员的感知能力与理解能力，进而导致作业人员的情景意识能力下降。基于这一影响机制选取相应主客观指标所建立的XGBoost模型验证率达到88.90%，表明该模型可以对作业人员的情景意识能力进行评估预测。该模型更适用于控制室持续VDT的作业人员的情景意识评估，为未来控制室的情景意识监测设备提供了算法基础，同时，所揭示的影响机制为情景意识领域的研究提供了理论基础。基于研究结果提出针对性的改善措施，旨在缓解控制室中的VDT疲劳，提高个人的情景意识水平，为相关领域的技术进步和理论深化贡献力量。

While the introduction of intelligent control systems has improved the safety of industrial system field equipment, it has also increased the demand for situational awareness among control room operators. With the dramatic increase in the amount of information on the interface and the increase in the difficulty of the operation and other factors, the fatigue of the control room operators is accelerated, and the level of personal situational awareness is also affected, which gradually reduces the ability of the operators to perceive and understand the emergencies they are facing, and ultimately results in human factors errors. At present, VDT fatigue, as the main factor affecting situational awareness in control rooms, has been less studied, especially for control rooms in coal mines, power stations and other related industries. Based on this, this paper uses EEG, eye movement and other multimodal data to explore the mechanism of VDT fatigue on situational awareness of operators in control rooms, and establishes an assessment model of situational awareness based on the subjective and objective data obtained, and finally makes recommendations for VDT operations in control rooms based on the results of the study.

In this paper, E-Prime software is used to present the experimental materials of situational awareness, 19 control room operators are selected as subjects, and situational awareness measurement experiments are carried out before and after the operators' job operations, and relevant data are collected with physiological instruments such as EEG and eye movement. The data related to situational awareness of the operators were pre-processed, and then SPSS software was used to statistically analyse each segment of the data, select the optimal indicators as the input of the model based on the significance and relevance of the data, and select the objective data as the output, so as to construct a situational awareness assessment model with multimodal data fusion. The results of the study show that there are significant changes in subjective and objective data, and it can be inferred that the subjects have produced VDT fatigue. Combining subjective data and EEG data, it can be found that the fatigue felt by the operators in the control room is mainly active fatigue caused by accumulation of cerebral and visual loads, and that this active fatigue will affect the operators' perceptual and comprehension abilities, which will lead to a decline in the situational awareness ability of the operators. This active fatigue will affect the perception and comprehension ability of the operators, which will lead to the reduction of their situational awareness. The validation rate of the XGBoost model based on the selection of subjective and objective indicators reaches 88.90%, which indicates that the model can assess and predict the situational awareness ability of operators. The model is more suitable for assessing the situational awareness of operators in the control room with continuous VDT, which provides an algorithmic basis for future situational awareness monitoring equipment in the control room, and at the same time, the revealed influencing mechanism provides a theoretical basis for research in the field of situational awareness. Based on the results of the study, targeted improvement measures are proposed with the aim of alleviating VDT fatigue in control rooms, improving the level of situational awareness of individuals, and contributing to the technological progress and theoretical deepening in related fields.

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