Danger Detection during Fight against Compartment-Fire Using Moving Averages in Temperature Recordings

Michel Lebey^*, Amal Bouaoud, Eloi Lambert

Laboratoire Ondes et Milieux Complexes (LOMC, UMR CNRS 6294), University of Le Havre, Le Havre, France.

DOI: 10.4236/wjet.2014.23B006                

Abstract

In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere through many kinds of ducts, which leads to the propagation of the combustion by the creation other fires in places which may be far away from the initial fire. In this paper, we present a new approach of the problem, which allows to better follow the fire behavior and especially to detect the dangers that may appear and endanger firefighters. This approach consists in a mathematical analysis based on the comparison of moving averages centered in the past, calculated on the temperature recordings of the smokes. As a consequence, this method may allow to improve decision support in real time and therefore to improve the security and the efficiency of firefighters in their operations against that kind of fires.

Keywords

Compartment Fire, Decision Support in Real Time, Moving Average, Danger Detection

Conflicts of Interest

The authors declare no conflicts of interest.

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