Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/121084
Title: Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review
Author: Fonollosa, Jordi
Solórzano, Ana
Marco Colás, Santiago
Keywords: Detectors
Foc
Monòxid de carboni
Fum
Detectors
Fire
Carbon monoxide
Smoke
Issue Date: 11-Feb-2018
Publisher: MDPI
Abstract: Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative.
Note: Reproducció del document publicat a: https://doi.org/10.3390/s18020553
It is part of: Sensors, 2018, vol. 18, num. 2, p. 553-591
Related resource: https://doi.org/10.3390/s18020553
URI: http://hdl.handle.net/2445/121084
ISSN: 1424-8220
Appears in Collections:Articles publicats en revistes (Electrònica)
Articles publicats en revistes (Institut de Bioenginyeria de Catalunya (IBEC))

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