Researchers at the National Institute for Occupational Safety and Health (NIOSH) are advancing the emerging technology of electromagnetic proximity detection, which provides a promising means of protecting workers around any machinery that presents striking, pinning or entanglement hazards. This technology is particularly applicable to mobile underground mining equipment such as remote-control continuous mining machines, which offer perhaps the most difficult safety challenges in the mining industry. The operators of these machines must maintain constant vigilance to keep themselves and others near the machine safe. Tragically, striking and pinning accidents involving continuous mining machines occur every year causing severe injuries and claiming lives. Proximity detection technology has been effectively implemented for other types of equipment in underground and surface mining as well as in other industries. However, applying this technology to remote-control continuous mining machines presents uniquely difficult challenges. Due to visibility and space limitations, the machine operator must routinely work in very close proximity to the machine. In order to protect miners without preventing them from doing their jobs or causing nuisance alarms, NIOSH is now developing intelligent proximity detection technology. This technology accurately determines worker position relative to the machine and responds by intelligently issuing situation-specific alarms to warn the operator or disabling situation-specific machine functions to protect the operator from machine movements that could result in injury. In this paper, the authors review existing proximity warning technologies, describe ongoing NIOSH research on an intelligent proximity warning system, and summarize current test results. The NIOSH-developed intelligent system has the potential to have a significant impact on the mining industry by greatly advancing the state-of-the-art in proximity detection technology, leading to increased operator safety, and reducing the frequency of injuries and fatalities.
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