Lutz Timothy J, DuCarme Joseph P, Smith Adam K, Ambrose Dean
Mine Safety and Health Research, National Institute for Occupational Safety and Health, Pittsburgh, USA.
J Environ Health Sci. 2016 Dec 27;2(6):1-6. doi: 10.15436/2378-6841.16.1131.
According to Mine Safety and Health Administration (MSHA) data, during 2008-2012 in the U.S., there were, on average, 65 lost-time accidents per year during routine mining and maintenance activities involving remote-controlled continuous mining machines (CMMs). To address this problem, the National Institute for Occupational Safety and Health (NIOSH) is currently investigating the implementation and integration of existing and emerging technologies in underground mines to provide automated, intelligent proximity detection (iPD) devices on CMMs. One research goal of NIOSH is to enhance the proximity detection system by improving its capability to track and determine identity, position, and posture of multiple workers, and to selectively disable machine functions to keep workers and machine operators safe. Posture of the miner can determine the safe working distance from a CMM by way of the variation in the proximity detection magnetic field. NIOSH collected and analyzed motion capture data and calculated joint angles of the back, hips, and knees from various postures on 12 human subjects. The results of the analysis suggests that lower body postures can be identified by observing the changes in joint angles of the right hip, left hip, right knee, and left knee.
根据美国矿山安全与健康管理局（MSHA）的数据，2008年至2012年期间，在美国，涉及遥控连续采煤机（CMM）的常规采矿和维护活动中，平均每年有65起造成误工的事故。为解决这一问题，美国国家职业安全与健康研究所（NIOSH）目前正在研究地下矿山现有和新兴技术的实施与整合，以便在连续采煤机上配备自动化、智能接近检测（iPD）设备。NIOSH的一个研究目标是通过提高其跟踪和确定多名工人的身份、位置和姿势的能力，以及选择性地禁用机器功能来保障工人和机器操作员的安全，从而增强接近检测系统。矿工的姿势可通过接近检测磁场的变化来确定与连续采煤机的安全工作距离。NIOSH收集并分析了运动捕捉数据，并计算了12名人体受试者各种姿势下背部、臀部和膝盖的关节角度。分析结果表明，通过观察右髋、左髋、右膝和左膝的关节角度变化，可以识别下半身姿势。
