大气与环境光学学报2021，Vol.16Issue(4)：349-357,9.DOI:10.3969/j.issn.1673-6141.2021.04.007
基于多传感器融合技术的微型空气质量监测系统优化设计
Optimization Design of Miniature Air Quality Monitoring System Based on Multi-Sensor Fusion Technology
摘要
Abstract
In view of the challenge that the National Ambient Air Quality Monitoring Station(NAAQM-S)is not suitable for large area distribution due to its large volume and high cost,a miniature air quality monitoring system is developed to monitor the concentrations of CO,NO2,O3,SO2,PM2.5 and PM10 in atmosphere.Electrochemical gas sensors and optical particle counter are adopted to measure the concen-tration of air pollutants and particles respectively in the system.Considering that the sensor is vulnerable to the influcence of temperature and humidity of atmosphere when measuring the concentration of pollutants,the measurement results are modified through the temperature and humidity compensation algorithm based on the multi-sensor fusion technology.Then the modified measurement results are compared with the data released by NAAQMS,and it is shown that there is a strong correlation between the two data.Compared with the data obtained from NAAQMS,the correlation coefficient for 10 days monitoring data obtained from the developled system is better than 0.7.After the algorithm correction,the correlation coefficien-t of some pollutants,such as PM2.5,can even be improved to 0.9.The air quality monitoring system is robust and small in size,which is suitable for long-term and large area distributed network monitoring of environmental air pollutants.关键词
空气质量监测/优化设计/多传感器融合/小型化Key words
air quality monitoring/optimization design/multi-sensor fusion/miniaturization分类
资源环境引用本文复制引用
王玉钟,王焕钦,胡俊涛,桂华侨..基于多传感器融合技术的微型空气质量监测系统优化设计[J].大气与环境光学学报,2021,16(4):349-357,9.基金项目
Supported by the National Key Research and Development Program of China(国家重点研究发展计划,2016YFC0201000),the Natural Science Foundation of China(国家自然科学基金,61673368),the Science and Technological Fund of Anhui Province for Outstanding Youth(安徽省优秀青年科学基金,1808085J19). （国家重点研究发展计划,2016YFC0201000）
