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Multiple type discriminating mine fire sensors.

Authors
Edwards-JC; Franks-RA; Friel-GF; Lazzara-CP; Opferman-JJ
Source
Trans Soc Min Metal Explor 2003 Dec; 314:166-171
NIOSHTIC No.
20024717
Abstract
Researchers determined that a selection of different types of fire sensors could be used to discriminate mine fires from nuisance emissions produced by diesel equipment. A neural network (NN) was developed for application to coal, wood, and conveyor belt fires in the presence of diesel emissions and was evaluated with the successful prediction of 22 out of 23 mine fires based on a fire probability determination. The optimum sensor selection for the NN was composed of a carbon monoxide sensor, two types of metal oxide semiconductor sensors, and an optical-path smoke sensor.
Keywords
Underground-mining; Mine-fires; Diesel-emissions; Coal-mining; Safety-research; Sensors; Hazards
Contact
NIOSH Pittsburgh Research Laboratory, P.O. Box 18070, Pittsburgh, PA 15236
CODEN
TMENAE
CAS No.
630-08-0
Publication Date
20031201
Document Type
Journal Article
Editors
Yernberg-WR
Fiscal Year
2004
NTIS Accession No.
NTIS Price
ISSN
1075-8623
NIOSH Division
PRL
Source Name
Transactions of the Society for Mining, Metallurgy, and Exploration
State
PA
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