井下生产操作实践中疲劳状态感知

刘毅; 张纬韬; 张帆

doi:10.13272/j.issn.1671-251x.17875

井下生产操作实践中疲劳状态感知

doi: 10.13272/j.issn.1671-251x.17875

中国矿业大学(北京) 机电与信息工程学院, 北京 100083

基金项目:

国家重点研发计划项目（2016YFC0801806）；中国矿业大学（北京）教学内容更新与教学方法改革研究项目（J210418）；中央高校基本科研业务费资助项目（2021YJSJD24）。

详细信息

作者简介:
刘毅(1973-),男,山西临汾人,副教授,博士,研究方向为矿井通信与定位、矿井监控与监视,E-mail:liu_y@sina.com。

中图分类号: TD67
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- 被引次数: 0
出版历程
- 收稿日期: 2021-12-16
- 修回日期: 2022-01-30
- 网络出版日期: 2022-03-01

Fatigue state perception in underground production operation practice

School of Mechanical Electronic and Information Engineering, China University of Mining and Technology(Beijing), Beijing 100083, China

摘要

摘要: 煤矿事故中人为因素引发的事故主要由井下作业人员疲劳和注意力不集中引发的误操作造成。现有基于生理信号或眼部图像的人员疲劳检测方法存在实施复杂、适应性差、准确率低、易漏报和误报等问题。针对上述问题，设计了一种基于头部姿态监测的井下人员疲劳状态感知装置。当井下人员处于疲劳状态时，会产生头部下垂动作，大脑通过耳蜗感知到头部失去平衡，为了恢复平衡和保持清醒，大脑会控制颈部进行恢复性抬头动作，从而形成一个周期性点头动作。在安全帽上安装九轴姿态传感器采集角速度、加速度、磁场强度，通过数据融合得到头部姿态数据，利用四元数法解算头部姿态角，并根据头部姿态角捕捉点头动作，当单位时间内点头动作占比超出阈值，则判断人员处于疲劳状态，发出声光预警，并通过无线方式向地面监控终端发送预警信号。实验结果表明，该装置能准确获取头部姿态角，捕捉疲劳特征动作，并有效判断井下人员是否处于疲劳状态。该装置具有体积小、质量轻、功耗低、易于实施等特点，可为生产操作实践中操作疲劳监测提供技术借鉴。
- 疲劳状态感知 /
- 头部姿态 /
- 点头动作 /
- 九轴姿态传感器 /
- 四元数
Abstract: The accidents caused by human factors in coal mine accidents are mainly caused by misoperation caused by fatigue and inattention of underground operating personnel. The existing personnel fatigue detection method based on physiological signals or eye images has the problems of complex implementation, poor adaptability, low accuracy and easy false negatives and false positives. In order to solve the above problems, a perception device of fatigue state of underground personnel based on head posture monitoring is designed. When the underground personnel is in a fatigue state, the head droop motion will occur, and the brain senses the head imbalance through the cochlea. In order to restore balance and keep awake, the brain will control the neck to carry out recovery head-raising motion, thus forming a periodic nodding motion. A nine-axis posture sensor is installed on the safety helmet to collect angular velocity, acceleration and magnetic field strength, and head posture data is obtained through data fusion. The head posture angle is calculated by using the quaternion method, and nodding motion is captured according to the head posture angle. When the proportion of nodding motion in unit time exceeds a threshold value, it is judged that the personnel is in a fatigue state, voice and light early warning occurs and an early warning signal is sent to a monitoring terminal on the ground through a wireless mode. The experimental results show that the device can accurately obtain the head posture angle, capture the fatigue characteristic motion, and judge whether the underground personnel is in a fatigue state effectively. The device has the characteristics of small volume, light weight, low power consumption and easy implementation, which can provide technical reference for operation fatigue monitoring in production operation practice.
- fatigue state perception /
- head posture /
- nodding motion /
- nine-axis posture sensor /
- quaternion

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参考文献(16)

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