Abstract
In this study, a method is presented for estimating the number density of fine dust particles (the number of particles per unit area) through numerical simulations of multiply scattered ultrasonic wavefields. The theoretical background of the multiple scattering of ultrasonic waves under different regimes is introduced. A series of numerical simulations were performed to generate multiply scattered ultrasonic wavefield data. The generated datasets are subsequently processed using an ultrasound data processing approach to estimate the number density of fine dust particles in the air based on the independent scattering approximation theory. The data processing results demonstrate that the proposed approach can estimate the number density of fine dust particles with an average error of 43.4% in the frequency band 1–10 MHz (wavenumber × particle radius ≤ 1) at a particle volume fraction of 1%. Several other factors that affect the accuracy of the number density estimation are also presented.
Highlights
Airborne particulate matter, such as fine dust, is a global concern owing to its detrimental impact on human health [1,2,3,4]
The remainder of this article is organized as follows: in Section 2 the theoretical background on the multiple scattering of acoustic waves in a discrete random medium is introduced; Section 3 describes the proposed ultrasound data processing approach to estimate the number density of fine dust particles; Section 4 provides details on the numerical simulations of multiply scattered ultrasonic wavefields; in Section 5 numerical simulation results of the number density estimation are demonstrated; in Section 6 we discuss several factors that affect the accuracy of the number density estimation
We focus on using coherent waves under Regimes 1 and 2 to estimate the number density of fine dust particles in the air, considering that acoustic wave propagation in the air
Summary
Airborne particulate matter, such as fine dust, is a global concern owing to its detrimental impact on human health [1,2,3,4]. We propose a mechanical wave-based method to estimate the number density of fine dust particles (the number of particles per unit area) in air. The proposed method uses ultrasonic acoustic waves multiply scattered by fine dust particles in the air and the number density of fine dust particles is computed by processing the measured multiple scattering data based on the independent scattering approximation theory. The unique contributions of this study are: (1) the effective use of mechanical waves to estimate the number density of fine dust particles, (2) development of an ultrasonic wavefield data processing technique that directly computes the number density from measured wavefield data, and (3). The remainder of this article is organized as follows: in Section 2 the theoretical background on the multiple scattering of acoustic waves in a discrete random medium is introduced; Section 3 describes the proposed ultrasound data processing approach to estimate the number density of fine dust particles; Section 4 provides details on the numerical simulations of multiply scattered ultrasonic wavefields; in Section 5 numerical simulation results of the number density estimation are demonstrated; in Section 6 we discuss several factors that affect the accuracy of the number density estimation
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