Analysis of the Impact of Multiwavelength Light Scattering on the Detection of the Sauter Mean Diameter of Fire Smoke Particles

Contemporary fire smoke detectors predominantly utilise the intensity of scattered light to identify fire smoke and initiate fire alarms. However, particles from non-fire aerosols may trigger false fire alarms, and response times for black and white smoke may be inconsistent due to variations in the refractive index. To address the limitations of existing fire smoke detection techniques in terms of reducing the false alarm rate and improving the detection sensitivity, this study aims to optimise the performance of fire smoke detectors by introducing a three-wavelength Sauter mean diameter (SMD) detection method based on Mie scattering theory and a three-stage model. Specifically, a third-wavelength correction channel is added on the basis of the dual-wavelength design, and the effects of the aerosol particle size distribution, refractive index and scattering angle on the detection performance are evaluated via simulation analysis. The results show that the ability of particle detection can be improved by increasing the intermediate wavelength, and the attenuation of large-angle scattering signals can be compensated by the weighting function. Compared with that of the traditional dual-wavelength method, the average relative error of detection can be reduced from 41% to 8.9% when the three-wavelength Sauter mean diameter methods of 450 nm, 550 nm and 950 nm are used, which effectively balances the detection sensitivity of black smoke and white smoke.