ABSTRACT
Methane detection in underground coal and other gassy mines traditionally done with point-type sensors or by certified examiners using handheld meters. To provide a sufficient margin of safety, machine-mounted point sensors shut down equipment at methane concentrations of 1 or 1.5%, yet many mine fires and explosions have shown that point sensors may not be capable of detecting explosive methane clouds. The 2010 explosion at the Upper Big Branch mine in West Virginia, USA, is one such example that killed 29 miners. Researchers are using multi-point methane readings, CFD, and 3-D modeling to produce the real-time methane distribution cloud and visualization through virtual and augmented reality (VR and AR). Knowing the position of the shearer, shields and other ignition sources creates a proximity detection model for the methane cloud that will automatically shut off the shearer or other equipment before an explosion can happen.
