Advanced fire detection algorithms using data from the home smoke detector project

The primary goal of this study is to develop fire detection algorithms for use in residential occupancies that reduce the nuisance sensitivity and detect fires at least as fast as conventional ionization and photoelectric detectors. An analysis is conducted using he output from ionization, photoelectric and carbon monoxide (CO) detectors, and a thermocouple measurement from 32 fire tests and 11 nuisance tests. Eight parameters are identified from the data collected from the four sensors by considering the magnitude and rate of rise of the output from each sensor. Algorithms are developed from these eight parameters using three approaches: analyzing the value of a single parameter relative to the response of commercial detectors given fire and nuisance sources, conducting the same analysis with two or three parameters and conducting the same analysis with a principal component analysis (PCA) of all eight parameters. The best fire sensitivity and nuisance immunity was observed for three algorithms: temperature rise and CO; CO and ionization detector; and temperature rise, CO and ionization detector. (C) 2004 Elsevier Ltd. All rights reserved.