Optical Physical Parameters of Fine Particulate Matter Based on Light Scattering Method

Author:

Xie Peng1,Liu Juntong2,Chen Kechao2

Affiliation:

1. Faculty of Science, Beijing University of Technology, Beijing, 100124, China

2. Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology (Beijing Municipal Institute of Labor Protection), Beijing, 100054, China

Abstract

Following the Internet, the Internet of Things (IoT) has become another revolutionary technology in recent years. In recent years, Internet of Things technology has been applied to various industries such as agricultural production, intelligent transportation and industrial production, including the wireless system network under the Internet of Things technology. The problem of particulate matter pollution has become more and more concerned. However, how to quickly and accurately detect particulate matter concentration has become a research hotspot. The traditional filter membrane weighing method and ray absorption method have many limitations, which cannot meet the requirements of fast and accurate. The measurement of particle mass concentration by light scattering method is a non-contact detection method of particle mass concentration. In this paper, light scattering methods are combined with the theory of IoT wireless systems to discuss the photophysical parameters of tiny particles, such as particle size and density. This paper mainly studies the formation mechanism, particle detection principle and numerical simulation, and the data intelligent analysis of the optical and physical parameters of the particles. The particle size distribution, average particle size and density were obtained by CCD photosensor experiment. The experimental results show that the optical parameters of different particle sizes are accurate and reliable.

Publisher

American Scientific Publishers

Subject

Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials

Reference23 articles.

1. The generalised product moment distribution in samples from a normal multivariate population;Wishart;Biometrika,1928

2. Normal multivariate analysis and the orthogonal group;James;The Annals of Mathematical Statistics,1954

3. Random matrix theories in quantum physics: Common concepts;Guhr;Phys. Rep. V,1998

4. A review of particle measurement methods based on light scattering;Chao;Laser and Infrared,2015

5. A new type of laser dust concentration online measuring instrument system design;Wei;Computer Programming Skills and Maintenance,2021

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