An algorithm for improving the reliability of detection with processing of multiple sensors'signal

Abstract

Recent surveys show that most of the false alarms of fire alarm systems are given by deceptive phenomena caused by human actions, such as cigarette smoking and cooking. Software-controlled systems have a potential ability in increasing the reliability of detection signals by data processing. However, it is rather difficult to distinguish an early stage fire from those deceptive phenomena only by processing the data of a single sensor. The authors' new algorithm utilizes the signals from three different sensors, i.e. temperature, smoke and gas (CO) concentration. Incorporating a mathematical fire model, these signals are translated into source parameters such as heat release rate, and smoke and gas generation rates. The conditions of the fire are then analyzed using the cross-correlation function between these source parameters. Testing the algorithm has been done using some experimental data and a promising result has been obtained.