journal article·2023-04-30Open access

Experimental Study on Particle Size Distribution Characteristics of Aerosol for Fire Detection

Wen-Hui Dong, Xue-Er Sheng, Shu Wang, Tian Deng

Applied Sciences· Volume 13· Issue 9

Abstract

Current optical fire smoke detectors use scattering light intensity as an indicator of smoke concentration and trigger fire alarms when the intensity exceeds a threshold value. However, such detectors are prone to false alarms caused by non-fire aerosols since both fire smokes and non-fire aerosols scatter light. Thus, in order to reduce false alarms caused by non-fire aerosols such as dust and water vapor, fire detectors must be capable of distinguishing fire smoke from non-fire aerosols. Since the light scattering signals depend on the particle size information of aerosols, it is essential to study and characterize the particle size distribution of fire smoke and non-fire aerosols for differentiating them. In this paper, a comprehensive aerosol experimental platform is built to measure the particle size distribution of various typical fire smokes and non-fire aerosols. Through the conducted experiments, we note that there are significant differences in the particle size distributions of typical fire smokes and non-fire aerosols, with a boundary of about 1μm. The experimental results provide fundamental data support of the particle size distribution for developing a better fire detector that accurately identifies smoke.
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Research context

OpenAlex topics: Atmospheric aerosols and clouds · Fire Detection and Safety Systems · Fire effects on ecosystems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Shenyang Fire Science and Technology Research Institute of MEM, Shenyang 110034, China

School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China

Hubei Key Laboratory of Smart Internet Technology, Huazhong University of Science and Technology, Wuhan 430074, China

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China (NSFC) · the Fundamental Research Funds for the Central Universities of HUST

References (28)

Show source-provided references
1. Dual-wavelength optical sensor for measuring the surface area concentration and the volume concentration of aerosols10.1016/j.snb.2016.06.031 ↗
2. An optical fire detector with enhanced response sensitivities for black smoke based on the polarized light scattering10.1088/1361-6501/ab2e35 ↗
3. Schultze, T., Marcius, L., Krüll, W., and Willms, I. (2017, January 12–14). Polarised Light Scattering Analyses for Aerosol Classification. Proceedings of the 17th Suppression, Detection, and Signaling Research and Applications Conference, College Park, MD, USA.
4. A Sauter mean diameter sensor for fire smoke detection10.1016/j.snb.2018.11.021 ↗
5. On-line high-accuracy particulate matter monitoring technology using multi-channel scattering signals10.1364/OE.435894 ↗
6. Optical sensing of smoke using a polychromatic LED: Combustion material identification using HLS analysis10.1108/02602280410525986 ↗
7. Cole, M. (2009, January 8–10). Aerosol characterisation for reliable ASD operation. Proceedings of the 14th International Conference on Automatic Fire Detection, Duisburg, Germany.
8. Characterization of Smoke From Smoldering Combustion for the Evaluation of Light Scattering Type Smoke Detector Response10.1177/104239159200400103 ↗
9. Multi-angle Scattering Characteristic of test Fire Smoke and Typical Interference Aerosol10.1016/j.proeng.2011.04.684 ↗
10. Precise size distribution measurement of aerosol particles and fog droplets in the open atmosphere10.1364/OE.27.00A890 ↗
11. Philipp, J.B.H.A., Wedler, G., and Rosam, A. (2014, January 14–16). Pure optical false alarm resisting smoke detector. Proceedings of the 15th International Conference on Automatic Fire Detection, Duisburg, Germany.
12. Philipp, J.-B., Kirbach, K., Hofmann, M., Hopfe, A., Schank, M., Behrens, R., and Wedler, G. (2017, January 10–11). False Alarm Resisting Smoke Detector for Mobility Application. Proceedings of the International Aircraft Systems Fire Protection Working Group, Cologne, Germany.
13. Detection of spacecraft fire signatures and post-fire aerosols—Part I: Ground-based results10.1016/j.firesaf.2015.04.004 ↗
14. Greenberg, P.S., and Fischer, D.G. (2010, January 11–15). Advanced Particulate Sensors for Spacecraft Early Warning Fire Detection. Proceedings of the 40th International Conference on Environmental Systems, Barcelona, Spain.10.2514/6.2010-6243 ↗
15. Xiao, X., Deng, T., Zhu, M., and Wang, S. (2017, January 12–14). A Method for Fire Detecting by Volume and Surface Area Concentration Based on Dual Wavelengths. Proceedings of the 17th Suppression, Detection, and Signaling Research and Applications Conference, College Park, MD, USA.
16. On-line determination of the optical properties of particles produced by test fires10.1016/j.firesaf.2005.10.001 ↗
17. Optical Properties of Fire and Non-fire Aerosols10.1016/S0379-7112(96)00048-3 ↗
18. Jang, H.-Y., and Hwang, C.-H. (2023). Preliminary Study for Smoke Color Classification of Combustibles Using the Distribution of Light Scattering by Smoke Particles. Appl. Sci., 13.10.3390/app13010669 ↗
19. Light scattering intensity field imaging sensor for in-situ aerosol analysis10.1021/acssensors.0c00574 ↗
20. Optical aerosol sizing method without prior refractive index10.1016/j.measurement.2022.112072 ↗
21. Eliminating the effects of refractive indices for both white smokes and black smokes in optical fire detector10.1016/j.snb.2017.06.122 ↗
22. Li, L.B.C.A., Deng, T., Zeng, J., Xu, F.F., Yan, S., Wang, S., Cheng, W.Q., Zhu, M., and Xu, W.B. (2022). A Simple Optical Aerosol Sensing Method of Sauter Mean Diameter for Particulate Matter Monitoring. Biosensors, 12.10.3390/bios12070436 ↗
23. A miniaturized aerosol sizing sensor using light-scattering angular spectrum10.1016/j.optlaseng.2022.107257 ↗
24. Analysis of Dust Properties to Solve the Complex Problem of Non-fire Sensitivity Testing of Optical Smoke Detectors10.1016/j.proeng.2013.08.136 ↗
25. Krüll, W., Willms, H.I., Tobera, R., and Schultze, T. (2023, March 19). Characterization of dust aerosols in false alarm scenarios. Duisburg, 2014; Universität Duisburg-Essen. Available online: https://www.nfpa.org/-/media/Files/News-and-Research/Resources/Research-Foundation/Symposia/2015-SUPDET/2015-papers/SUPDET2015Kruellextendedabstract.ashx.
26. Fire Smoke Particle Size Distribution Measurement and Evolution Simulation
27. Fire Smoke Particle Size Distribution Evolution Under Brownian Coagulation
28. Dynamic smoke particle size distribution in test fire