Volume 66 Issue 10
Oct.  2022
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XU Xiao, CHI Shunxin, LI Xiang. Development of an Intelligent Metrological Platform for Particulate Matter Mass Concentration[J]. Metrology Science and Technology, 2022, 66(10): 71-76. doi: 10.12338/j.issn.2096-9015.2022.0178
Citation: XU Xiao, CHI Shunxin, LI Xiang. Development of an Intelligent Metrological Platform for Particulate Matter Mass Concentration[J]. Metrology Science and Technology, 2022, 66(10): 71-76. doi: 10.12338/j.issn.2096-9015.2022.0178

Development of an Intelligent Metrological Platform for Particulate Matter Mass Concentration

doi: 10.12338/j.issn.2096-9015.2022.0178
  • Received Date: 2022-07-22
  • Accepted Date: 2022-08-01
  • Available Online: 2022-09-13
  • Publish Date: 2022-10-18
  • The dust, smoke, fugitive dust and particulate matter in the ambient air generated by factories and mines are the focus of attention in the fields of labor protection, industrial emission control and ambient air pollution monitoring in my country, which also puts forward higher requirements for the verification and calibration of particulate matter concentration monitoring instruments. An intelligent metrological platform for mass concentration of particulate matters is developed based on the feedback control of dust generation, digital image processing and optical character recognition, in order to provide the universal hardware and software infrastructure for the verification and calibration of dust measuring instruments, PM2.5/PM10 mass concentration monitors and particulate matter sensors. By implementing the feedback control of dust generation, the standard deviation of the mass concentrations during 20 min is reduced from 3.6%~6.4% down to 0.3%~0.7%, and the range of the mass concentrations during 4 h is reduced from 1.9%~12% down to 0.6%~1.9%. By applying automated calibration procedure control and data acquisition, 88% of manual repetitive operations in the calibration of PM2.5/PM10 monitors, as well as all the manual processes in the verification and calibration of dust monitors, can be eliminated, with improved efficiency and data quality.
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