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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.
| Author(s): | Edwards-JC, Franks-RA, Friel-GF, Lazzara-CP, Opferman-JJ |
| Reference: | Trans Soc Min Metal Explor 2003 Dec 314:166-171 |
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