Abstract
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.
Highlights
Coal mining is a relatively dangerous industry compared to private industry[1], but is a key component to the national energy strategy[2]
One of the primary pieces of equipment used during underground coal production is the continuous mining machine (CMM)
To improve the accuracy and performance, information about worker posture could be used by CMM proximity detection systems
Summary
Coal mining is a relatively dangerous industry compared to private industry[1], but is a key component to the national energy strategy[2]. One of the primary pieces of equipment used during underground coal production is the continuous mining machine (CMM). These machines are operated by remote control, and are used to extract coal from the working face through a rotary cutting drum and onboard articulating conveyor. Proximity detection systems warn and disable the machine if the operator intrudes into an unsafe area[4,5]. Further advances have been made through triangulating operator position and only disabling machine motions that are hazardous[6,7,8]. To improve the accuracy and performance, information about worker posture could be used by CMM proximity detection systems
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
