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为提高认知性视觉显示终端(VDT)持续监控作业系统的可靠性,需要有效预测和防范人因失误。基于N-back任务范式和持续操作测试(CPT)任务范式,设计并完成模拟认知性VDT持续监控作业的试验。根据试验数据分别对正确反应时、任务正确率等9个指标进行方差分析,构建三维度认知性VDT持续监控作业脑力负荷评估指标体系。训练BP神经网络,识别脑力负荷模式,建立认知性VDT持续监控作业人因可靠性评估模型。研究结果表明:通过正确反应时、心理努力、任务主观难度、注视时间、瞳孔直径、眨眼频率6个指标,对认知性VDT持续监控作业脑力负荷进行模式识别,其结果可信,且对实际作业干扰性小;用人因可靠性评估模型能有效预测人因失误。
In order to improve the reliability of the VDT continuously monitoring the operating system, it is necessary to effectively predict and prevent human error. Based on the N-back task paradigm and continuous operation test (CPT) mission paradigm, experiments were designed and completed to simulate cognitive VDT continuous monitoring operations. According to the test data, the analysis of variance (ANOVA) was carried out on nine indicators such as correct response and task correctness rate, respectively, and a three-dimensional cognitive VDT continuous monitoring task of mental workload assessment index system was constructed. Training BP neural network to identify the mental load model, the establishment of cognitive VDT continuous monitoring of human factors reliability assessment model. The results show that: through the correct response, psychological effort, subjective task difficulty, gaze time, pupil diameter, blink frequency of six indicators of cognitive VDT continuous monitoring operation of mental workload pattern recognition, the result is credible, and the actual Job interference is small; use of human reliability assessment model can effectively predict human error.