Advanced fire detection using multi-signature alarm algorithms

Abstract

The objective of this work was to assess the feasibility of reducing false alarms while increasing sensitivity through the use of combined conventional smoke detectors with carbon monoxide (CO) sensors. This was accomplished through an experimental program using both real (fire) and nuisance alarm sources. A broad selection of sources was used ranging from smoldering wood and flaming fabric to cooking fumes. Individual sensor outputs and various signal-conditioning schemes involving multiple sensors were explored. The results show that improved fire-detection capabilities can be achieved over standard smoke detectors by combining smoke measurements with CO measurements in specific algorithms. False alarms can be reduced while increasing sensitivity (i.e., decreasing the detection time for real fires). Patented alarm criteria were established using algorithms consisting of the product of smoke obscuration and the change in CO concentration. Alarm algorithms utilizing ionization detector smoke measurements proved to be more effective than measurements from photoelectric detectors.