Research on the aerosol identification method for the fire smoke detection in aircraft cargo compartment. (June 2022)

• Record Type: Journal Article
• Authors: Zheng, Rong; Lu, Song; Shi, Zhicheng; Li, Cong; Jia, Heming; Wang, Shuang
• Is Part Of: Fire safety journal. Volume 130(2022)
• Publication Date: 2022-06
• Subjects: Aircraft cargo compartment -- Smoke detection -- Light scattering -- False alarm -- Aerosol identification -- Asymmetry ratio; Fire prevention -- Periodicals; Incendies -- Prévention -- Recherche -- Périodiques; Fire prevention -- Research; Periodicals; 628.92205
• DOI: 10.1016/j.firesaf.2022.103574
• Languages: English
• ISSNs: 0379-7112

Abstract

Abstract: The false alarms produced by non-fire aerosols and low sensitivity to black smokes are two types of critical issues for optical fire smoke detectors, especially in the field of aviation. Dusts and droplets are considered as the typical nuisance aerosols in aircraft cargo compartment. In this paper, the effects of wavelength, polarization of light source and scattering angle were analyzed by numerical calculation and experimental measurement. The trend differentiation method based on asymmetry ratio (45/135) is proposed based on the numerical results. Detector prototypes with LEDs or LDs were developed for experimental verification analysis. Experimental results show that by using light sources at 405 nm with vertical polarization and 850 nm with horizontal polarization, the nuisance aerosols can be separated from fire smokes according to the relative size of asymmetry ratios, and furthermore white and black smokes also can be differentiated according to the size of asymmetry ratios. Therefore, the balanced response sensitivity to white and black smokes can be realized by adjusting the alarm response threshold accordingly. Highlights: Propose a trend differentiation method based on asymmetry ratio to distinguish different aerosol types. Reveal the rule that the asymmetry ratio of particles oscillates periodically with the size parameters. Obtain appropriate the smoke detection optical paths to discriminate fire smokes and nuisance aerosols.