Application of Multistep Inversion Method for Online Monitoring Aerosol Particle Size Distribution and Aerosol Concentration

Zhenzong He,Xingsi Han,Biao Zhang,Junkui Mao,Liang Xu

doi:10.1155/2020/1983460

Abstract

Aerosol concentration in the flow is usually time varying, and aerosol particle size distribution (PSD) is considered to be unchanged, which increases the difficulty of the measurement of aerosol PSD and concentration online. To solve these problems, a kind of multistep inversion method based on the angular light-scattering (ALS) signals is proposed. First, the aerosol PSD is estimated using shuffled frog-leaping algorithms (SFLAs) from relative ALS signals. Then, with aerosol PSD as priori information, the aerosol concentration is obtained by the Kalman filter (KF) algorithm, widely used in the real-time control system of industrial facilities for its ability of fast predictions. The result reveals that the performance of the improved SFLA is better than that of the original SFLA in solving the aerosol PSD. Moreover, in studying the aerosol concentration, more accurate results can be obtained with larger standard deviation of process noise or smaller standard deviation of measurement noise, while decreasing sampling time interval can improve the accuracy of retrieval results and reduce time delay to a certain degree. So, to improve retrieval accuracy, the noise should be controlled, and appropriate sampling time interval should be selected. All the numerical simulations confirm that the methodology provides effective and reliable results in real-time estimating.

Highlights

Aerosols usually play a pivotal role in determining the properties of the atmosphere, e.g., by reducing visibility or affecting the net radiative fluxes and temperature [1,2,3]
In studying the aerosol concentration, more accurate results can be obtained with larger standard deviation of process noise or smaller standard deviation of measurement noise, while decreasing sampling time interval can improve the accuracy of retrieval results and reduce time delay to a certain degree
The angular light-scattering (ALS) method combined with Kalman filter algorithm can be proposed as a kind of effective and reliable measurement technique to study the real-time estimation of aerosol concentration

Summary

Introduction

Aerosols usually play a pivotal role in determining the properties of the atmosphere, e.g., by reducing visibility or affecting the net radiative fluxes and temperature [1,2,3]. In the past few years, the optical measurement method (e.g., spectral extinction method, angular light-scattering method, diffraction lightscattering method, dynamic light-scattering method, laserinduced incandescence method, and laser-induced breakdown spectroscopy method) has been widely utilized to study the properties of particle system owing to offering a useful and effective approach to characterize a large number of industrial production processes. In the author’s previous work [23, 24], the ALS method combined with inverse radiative problem technique is successfully applied to study the PSD and optical constants. The convergence accuracy and robustness of the ALS method was proved to be better than that of the spectral extinction method

Methods

Results

Conclusion