~煤矿企业属于劳动密集型行业，井下恶劣复杂的环境条件与繁重且单一化的劳动易使矿工注意力下降，导致不安全行为。矿井掘进面属于煤矿危险事故频发区，掘进司机在作业过程中受到体力和脑力的双重负荷。目前，在煤矿安全领域，研究者多致力于噪声环境对矿工的影响以及矿工危险感知方面的研究，但专门针对掘进司机这类特殊工种的研究相对较少。因此，本文对掘进司机在掘进面噪声环境下的危险感知能力进行研究，探讨掘进面噪声环境下掘进司机的各项心理、行为、眼动与生理指标的变化，分析掘进司机危险感知能力受掘进面噪声影响的情况，期望将掘进面噪声控制及预防纳入到煤矿安全管理体系之中，对煤矿安全管理提供借鉴。
本文设计了两个实验，实验一为掘进面噪声对掘进司机注意力影响实验。运用舒尔特方格软件与Axure仿真模拟掘进操作系统，通过还原真实场景，采集掘进司机的反应时长、错误次数、超时次数与正确率4个指标进行统计分析。实验二为掘进面噪声对掘进司机危险感知影响实验。收集煤矿掘进司机在日常生产作业中含有一定危险性与危险点的场景，在眼动仪上随机呈现静态漫画（有危险）与真实场景（有危险和无危险）三类图片，被试根据图片所呈现的线索判断该场景是否存在危险，使用Tobii T60XL眼动仪与Biopac多导生理仪采集掘进司机对危险场景的心理、行为、眼动、生理等各项指标进行分析。最后，将掘进面危险进行分级并运用支持向量机（SVM）对实验的样本数据进行训练。
结果表明：（1）对比两种实验环境下掘进司机的各项实验指标，发现掘进司机的注意力、反应力在有无掘进面噪声环境下差异显著，但掘进司机的操作正确率在有无掘进面噪声环境下差异不显著。（2）掘进面噪声会降低掘进司机的危险感知能力。有掘进面噪声时，掘进司机发现危险点的时间与注视点个数增加、首个注视点到下次鼠标点击的时间增加、心率与心率变异性会发生明显变化，但血压的变化不显著。由量表数据可得：注意力量表反映掘进司机在生产作业过程中自身的注意力与感知能力依旧存在差异；主诉症状量表反映掘进面噪声能诱发掘进司机的疲劳症状；情绪量表反映有掘进面噪声下掘进司机愤怒、焦虑、恐惧等情绪的变化较为显著。（3）选取的实验指标对掘进司机危险感知能力的预测是可行的。

~Coal mining enterprises are labor-intensive industries. The harsh and complex environmental conditions and heavy and singular labor in underground mines can easily reduce the attention of miners and lead to unsafe behaviors. The mine tunnel face belongs to the area where dangerous accidents frequently occur in coal mines, and the tunneling driver is subjected to the dual load of physical and mental strength during the operation. At present, in the field of coal mine safety, researchers are mostly devoted to the research on the impact of noise environment on miners and the miners’ hazard perception, but there is less research on special types of work such as tunneling drivers. Therefore, this paper studies the danger perception ability of the tunneling drivers under the noise environment of the tunnel surface, discusses the changes of various psychological, behavioral, eye movement and physiological indicators of the tunneling drivers under the noisy environment of the tunnel surface, and analyzes the impact of the tunneling driver’s danger perception ability on the tunnel. With regard to the impact of surface noise, it is expected that the control and prevention of tunneling surface noise will be incorporated into the coal mine safety management system to provide a reference for coal mine safety management.
Two experiments are designed in this paper. The first experiment is an experiment on the influence of tunneling surface noise on the attention of tunneling drivers. Using Schulte Grid software and Axure to simulate the tunneling operating system, by restoring the real scene, four indicators including the reaction time, the number of errors, the number of timeouts and the correctness of the tunneling drivers are collected for statistical analysis. The next experiment is an experiment on the impact of tunneling surface noise on the danger perception of tunneling drivers. Collect scenes with certain dangers and dangerous points in the daily production operations of coal mine boring drivers, and randomly present three types of pictures of static cartoons (dangerous) and real scenes (dangerous and non-dangerous) on the eye tracker. Participants are based on the pictures. The clues presented are used to judge whether the scene is dangerous. Tobii T60XL eye tracker and Biopac physiological multi-conductor are used to collect and analyze the psychology, behavior, eye movement, physiology and other indicators of the dangerous scene. Finally, the hazards of the tunneling face are classified and the support vector machine (SVM) is used to train the sample data of the experiment.
The results show that: (1) Comparing the various experimental indicators of the tunneling drivers in the two experimental environments, it is found that the attention and reaction of the tunneling driver are significantly different under the noise environment of the tunneling surface, but the accuracy of the tunneling driver's operation is The difference is not significant under the noise environment of the tunneling face. (2) The noise of the tunneling surface will reduce the tunneling driver's perception of danger. When there is tunneling surface noise, the time for the tunneling drivers to find the dangerous point and the number of fixation points increase, and the time from the first fixation point to the next mouse click increases. The heart rate and heart rate variability will change significantly, but the blood pressure will not change significantly. The scale data can be obtained: the attention strength scale reflects that there are still differences in the attention and perception abilities of the tunneling drivers during the production process; the main complaint symptom scale reflects that the noise of the tunneling surface can induce the fatigue symptoms of the tunneling driver; the emotion scale reflects that there are The anger, anxiety, fear and other emotions of the tunneling driver under the noise of the tunneling surface were changed significantly. (3) The selected experimental indicators are feasible to predict the risk perception ability of tunneling drivers.

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