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Modeling Situation Awareness on Alarm Displays in Nuclear Power Plants

机译:核电厂警报显示中的态势感知建模

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摘要

Human factors engineering is important and has been brought into the regulations for the operation of nuclear power plants. However, there is still a discrepancy between the regulations and the practices. In this study, the SEEV model was used as a framework to construct an analytical model for predicting situation awareness in terms of the gaze distribution percentage on alarm displays in nuclear power plants. Two similar multiple linear regression models were constructed and validated based on the data of eye-tracking from 40 participants. Results showed that these two models were consistent with the SEEV framework. The values of R-square for these two models were 0.78 and 0.83, whereas the values of predicted R-square were 0.77 and 0.72. The analytical model developed in this study should be a necessary complement to current practice of situation awareness measurement. In addition, through the model, the improvement of alarm display design can be achieved in a resource-effective manner.
机译:人为因素工程很重要,已被纳入核电厂运行的法规中。但是,法规与实践之间仍然存在差异。在这项研究中,SEEV模型被用作构建分析模型的框架,该模型用于根据核电厂警报显示器上的凝视分布百分比来预测态势感知。基于40位参与者的眼动数据,构建并验证了两个相似的多元线性回归模型。结果表明,这两个模型与SEEV框架一致。这两个模型的R平方值分别为0.78和0.83,而预测的R平方值分别为0.77和0.72。在这项研究中开发的分析模型应该是对现状意识衡量的当前实践的必要补充。此外,通过该模型,可以以资源有效的方式实现警报显示设计的改进。

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