Title: Air harmful gas concentration monitoring method based on particle filter algorithm

Authors: Zhengyan Qin

Addresses: Department of Data Information, Changjiang Polytechnic, Wuhan 430074, China

Abstract: In order to solve the problem of poor accuracy of traditional air harmful gas concentration monitoring, an air harmful gas concentration monitoring method based on particle filter algorithm is proposed. The state space model of air harmful gas distribution is constructed, and the posterior probability density function is obtained by pushover estimation. The gas concentration to be measured is obtained by particle filter. According to the transition frequency, the second harmonic signal characteristics of harmful air gases are described by Lambert Beer's law. The Lorentz linear function is used to obtain the light intensity change after gas concentration modulation, obtain the relationship between the second harmonic and gas concentration, and realise the monitoring of harmful gas concentration in the air. The experimental results show that this method can improve the monitoring efficiency and accuracy of air harmful gas concentration, and the maximum monitoring accuracy is 98%.

Keywords: characteristic inversion; gas concentration; observation equation; transition frequency; Lorentz linear function.

DOI: 10.1504/IJETM.2022.124417

International Journal of Environmental Technology and Management, 2022 Vol.25 No.4, pp.298 - 309

Received: 28 Jul 2021
Accepted: 14 Dec 2021
Published online: 26 Jul 2022 *

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