Mine Fire Source Discrimination Using Fire Sensors and Neural Network Analysis
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2000/04/16
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Series: Mining Publications
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Description: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. [Description provided by NIOSH]
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Pages in Document:207-211
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NIOSHTIC Number:nn:20020920
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Citation:Combustion Fundamentals and Applications--Proceedings of the 2000 Technical Meeting of the Central States Section of the Combustion Institute, Indianapolis, Indiana. Pittsburgh, PA: The Combustion Institute, 2000 Apr; :207-211
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Federal Fiscal Year:2000
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Peer Reviewed:False
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Main Document Checksum:urn:sha-512:a5624589d9602080186c6334a9879776d0907d780098b023073fed3f844014900c44481a083c7ee874ac552ae64b04b7fe8f2d096c027b4ab5ab8c2bd713c879
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