Mining Publication: Mine Fire Source Discrimination Using Fire Sensors and Neural Network Analysis

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Original creation date: April 2000

Authors: JC Edwards, GF Friel, RA Franks, CP Lazzara, JJ Opferman

Conference Paper - April 2000

NIOSHTIC2 Number: 20020920

Combustion Fundamentals and Applications - Proceedings of the 2000 Technical Meeting of the Central States Section of the Combustion Institute (April 17-18, 2000, Indianapolis, IN); :207-211

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 carbon monoxide 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 carbon monoxide 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.

Image of publication Mine Fire Source Discrimination Using Fire Sensors and Neural Network Analysis
Conference Paper - April 2000

NIOSHTIC2 Number: 20020920

Combustion Fundamentals and Applications - Proceedings of the 2000 Technical Meeting of the Central States Section of the Combustion Institute (April 17-18, 2000, Indianapolis, IN); :207-211


Page last reviewed: 9/21/2012 Page last updated: 9/21/2012