Investigation of the performance and improvement of optical smoke detectors

Abstract

To reduce the false alarm from the smoke detectors, a series of experiments were conducted to collect and analyse the time series of signal pattern generated by the detectors under three fire categories - flaming fire (propanol), smoldering fire (cloth-cotton) and non-fire sources(joss stick and steam). The time series of each fire category was studied. Dissimilarity measure such as Euclidean Distance was used to discriminate the data collected. It is used to classify the fire category into fire class or non-fire class and enhance the effectiveness of the fire alarm judgment system. 30 sets of learning samples of each fire category (total: 120 experiments) are collected. It showed that the accuracy of smoke detector was over 80%. If multi-sensor (smoke and heat) detector was used, the accuracy was over 90%.