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Research On On-line Monitoring Technology Of Fine Industrial Dust

Posted on:2016-09-09Degree:MasterType:Thesis
Country:ChinaCandidate:Y F LuoFull Text:PDF
GTID:2191330470971246Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
Inhalable particles (PM10 and PM2.5) as the primary cause of hazy weather has became the main indicators of daily air quality. The inhalable particles is mainly discharged by energy industry and industrial production. On-line monitoring technology of fine industrial dust emissions is of impotant meaning to exhaust pollutant pollutant treatment and the implementation of national enviromental policies.This article summerized the status of dust concentration and particle size monitoring technology at home and abroad, an on-line monitoring system designed for fine industrial dust, based on research work of Mie scattering theory and Lambert beer law. First, elaborates the principle of measurement of the dust concentration and particle size distribution, the design scheme of the scattering intensity measuring system and the implementation of the components (lasers, optical path system, photoelectric detector, the signal processing unit and communication system) are given. Then to solve the problem for determining the concentration and size distribution of dust, the dust concentration measurement algorithms expouned and studied a particle size distribution inversion algorithms based on artificial fish swarm algorithms (AFSA). Finally, made a numerical simulation about the light scattring properties of fine dust discharged by coal plant and how the wavelength of incident light, relative refractive index and particle size influence on scattered light intensity distribution, the result of numerical simulation of particle size distribution algorithm based on AFSA obtained. The result of numerical simulation experiments verified the effectiveness of measuring method in monitoring system of this paper.
Keywords/Search Tags:industrial dust, on-line monitoring, Mie theory, inversion algorithm, AFSA
PDF Full Text Request
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