A Visual Warning System for the Identification of Proximity Detection Events around a Continuous Mining Machine

Abstract

Underground mobile mining machines pose a difficult safety challenge since their operators generally work in close proximity to these machines in very restricted spaces. Intelligent software for use with electromagnetic proximity detection systems has been developed that can accurately locate workers around mining machinery in real time. If a worker is located too close to the machine, the machine’s operation can be partially or completely disabled to protect the workers from striking, pinning, and entanglement hazards. Researchers have developed a visual method of relaying to the operators the interdiction of their machine operations by this intelligent proximity detection system. Several lighting sequence scenarios were human subject tested for effectiveness using a computer-based multimedia platform. Analysis of the test results indicates that a “fast flash” lighting arrangement is the most effective scenario based upon subject preference, rating, and accuracy of proximity intrusion location identification. This arrangement improves reaction time by 35%.