Citation

He Y, Zhang W, Yang W, Li Y. China Saf. Sci. J. 2019; 29(1): 43-48.

Copyright

(Copyright © 2019, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2019.01.008

PMID

unavailable

Abstract

In order to solve the problem of the high false alarm rates of the aircraft cargo compartment fire detectors caused by the dust and water vapor particles in the air, a multi-sensor composite aircraft cargo compartment fire detection method was worked out. Firstly, a composite fire detection device was built, including a temperature sensor, a CO sensor and a dual-wavelength photoelectric smoke sensor. A fire detection system software was designed. Then a large number of true and false fire source experiments were carried out to collect data on the parameter variation features of smoke, temperature and gas during the fire. Finally, the artificial neural network algorithm was used to perform fusion analysis of the collected data. The experimental data show that the alarm accuracy of the multi-sensor detection device embedded with dual-wavelength photoelectric smoke detector is significantly higher than that of traditional fire smoke detectors, and the relative error of interference source identification does not exceed 5.7%. © 2019 China Safety Science Journal. All rights reserved.

Language: zh