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Analysis of Fire and Non-Fire Signatures for Discriminating Fire Detection
Published
Author(s)
J A. Milke, T J. McAvoy
Abstract
The characteristics of an improved fire detector which promptly reacts to smoke while discriminating between airborne signatures from fire and non-fire sources can be identified by considering signature patterns of each group of sources. Discrimination is accomplished by comparing signature response patterns of each group of sources. Discrimination is accomplished by comparing signature response patterns from fire and environmental sources collected in small- and large-scale tests. Airborne signatures 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. The signatures are described in terms of light obscuration, temperature, CO, CO2, O2 concentrations and signals from metal oxide sensors. An expert system was developed by a neural network and a multivariate statistical method to distinguish between fire and non-fire sources. In addition, the presence of a flaming or non-flaming fire can be identified despite the injection of signatures from nuisance sources which could mask the fire signatures.
Proceedings Title
International Association for Fire Safety Science. Fire Safety Science. Proceedings. Fifth (5th) International Symposium.
Conference Dates
March 3-7, 1997
Conference Location
Melbourne,
Conference Title
Intl. Assoc. for Fire Safety Science, Boston, MA, Hasemi, Y., Editor(s), 819-828 pp, 1997
fire research, fire safety, fire science, fire detection, carbon dioxide, carbon monoxide, fire signatures, large scale fire tests, light obscuration, small scale fire tests, oxygen, temperature
Citation
Milke, J.
and McAvoy, T.
(1997),
Analysis of Fire and Non-Fire Signatures for Discriminating Fire Detection, International Association for Fire Safety Science. Fire Safety Science. Proceedings. Fifth (5th) International Symposium., Melbourne, , [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=916640
(Accessed December 15, 2024)