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Multivariate Methods for Fire Detection.


pdf icon Multivariate Methods for Fire Detection. (654 K)
Milke, J. A.; McAvoy, T. J.

NISTIR 6030; June 1997.

U.S./Japan Government Cooperative Program on Natural Resources (UJNR). Fire Research and Safety. 13th Joint Panel Meeting. Volume 2. March 13-20, 1996, Gaithersburg, MD, Beall, K. A., Editor(s), 411-418 pp, 1997.

Sponsor:

National Institute of Standards and Technology, Gaithersburg, MD

Available from:

National Technical Information Service
Order number: PB97-184204

Keywords:

fire safety; fire research; fire detection; fire detectors; small scale fire tests; large scale fire tests; experiments; light obscuration

Abstract:

Research is being conducted to describe the characteristics of an improved fire detector which promptly reacts to smoke while discriminating between smoke and odors from fire and non-fire sources. Discrimination is accomplished by comparing signature response patterns from fire and environmental sources collected in small- and large-scale tests. Smoke and odors are produced in the tests from a variety of conditions: flaming, pyrolyzing and heated samples, and nuisance sources, such as aerosols, household products and cooked food. Measurements include light obscuration, temperature, mass loss, CO CO2, O2 and oxidizable gas concentrations. The feasibility of an elementary expert system to classify the source of the signatures from small-scale experiments was demonstrated in the first phase. In the second and third phases, an expert system was developed by Multivariant statistical methods to distinguish between fire and non-fire sources. In addition, the presence of a fire could be identified despite the interjection of signatures from nuisance sources which could mask the fire signatures.