Inversion of particle size distribution using the artificial fish swarm algorithm

Author:

Shan Liang1,Xu Liang1,Cao Lixia2,Hong Bo1,Wang Daodang2,Guo Tiantai2,Kong Ming2

Affiliation:

1. Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering , 92270 China Jiliang University , Hangzhou , 310018 , China

2. College of Metrological Technology & Engineering , 92270 China Jiliang University , Hangzhou 310018 , China

Abstract

Abstract In the small-angle forward scattering technique, an inversion method of particle size distribution (PSD) using artificial fish swarm algorithm (AFSA) is proposed, which can acquire optimal characteristic parameters of the PSD. Simulations are performed to verify the effectiveness of AFSA, in which spheroidal particles of a unimodal distribution that conforms to Johnson’s S B {\mathrm{S}_{\mathrm{B}}} function is inversed at different levels of gaussian white noise. The comparison of the smooth objective function and non-smooth objective function of AFSA is conducted and discussed. The measurement system of the small-angle forward scattering based on Mie scattering theory is constructed and experiments are performed to verify the practicability of AFSA. A CCD sensor is adopted to receive the scattered light instead of the conventional photodetector. Pinhole is first proposed to replace standard particles and calibrate the measurement system, which can eliminate the influence of particle concentration. After the calibration experiments, the PSD of standardized polystyrene microspheres are measured and modified. Both the simulation and experiment results indicate that the PSD can be successfully inverted by AFSA with high reliability and stability in certain conditions, and the system calibration can further improve the inversion accuracy.

Funder

National Natural Science Foundation of China

Publisher

Walter de Gruyter GmbH

Subject

Electrical and Electronic Engineering,Instrumentation

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3. Inversion of particle size distribution based on iterative non-negative Philips-Twomey algorithm;Transactions of the Institute of Measurement and Control;2019-09-19

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