System Design Of Analyzer Based On Differential Optical Absorption Spectroscopy

The problem of air pollution has become a hot spot around the world.Smoke emissions from thermal power plants,chemical plants and other fixed pollution sources have become the focus of environmental protection and monitoring.With the country’s emphasis on environmental protection issues,SO₂and NO gases have caused widespread concern.NO is easily oxidized into NO₂in the air,SO₂and NO₂will react with water to form acid rain,which will cause great harm to humans and nature.In addition to reducing the emission of polluting gases,flue gas monitoring is also an important part of environmental protection governance.Ultraviolet gas analyzer has great advantages in industrial pollution gas monitoring due to its extremely high applicability and cost performance.In order to realize the on-line monitoring of SO₂and NO of fixed pollution sources,this paper designed a UV gas analyzer based on spectral absorption technology.This article designs a UV gas analyzer system based on UV differential absorption spectroscopy.According to national environmental protection standards,it formulates reasonable performance requirements.The optical system,circuit system,and mechanical structure of the UV gas analyzer are designed separately.A flue gas pretreatment system provides a stable sampling flue gas input to the analyzer to reduce the influence of unnecessary factors such as humidity and dust on the measurement results.In order to verify the feasibility of the analyzer,we also set up a measurement experiment system,which uses the analyzer to measure different concentrations of single-component SO₂and NO standard gases,and also measures the mixed gas of SO₂and NO.In the experimental result processing stage,we use Savitzky-Golay filtering and Fourier transform filtering to process the data,respectively.After comparison,it is found that the use of Savitzky-Golay filtering can achieve better noise reduction,and then the least squares calculation of the processed data can make the error of the measured value and the theoretical value smaller.