Mine Fire Source Discrimination Using Fire Sensors and Neural Network Analysis

Fire experiments were conducted in the Safety Research Coal Mine (SRCM) at the National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, with coal, diesel-fuel, electrical-cable, conveyor-belt, and metal-cutting fire sources to determine the response of fire sensors to products-of-combustion (POC). Metal oxide semiconductor (MOS) and smoke fire sensors demonstrated an earlier fire detection capability than a CO sensor. This capability was of particular significance for a conveyor-belt fire in which the optical visibility was reduced to 1.52 m with an increase in CO of less than 2 ppm at a distance of 148 m from the fire. Application of a neural-network program to the sensor responses from each type of fire source resulted in correct classifications of coal, diesel-fuel, cable, belt, and metal-cutting combustion with a mean of 96% of the test data correctly classified.