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Noise Reduction Method for Particle Measurement System using Beta-ray Absorption Method

베타선 흡수법을 이용하는 미세먼지 측정시스템을 위한 잡음제거 방법

  • 최훈 (동의대학교 전자공학과) ;
  • 손상욱 (미국 텍사스 오스틴 대학 전기&컴퓨터공학과) ;
  • 배현덕 (충북대학교 전자정보대학 전기공학과)
  • Received : 2012.07.09
  • Accepted : 2012.09.26
  • Published : 2012.11.01

Abstract

The Beta-ray absorption method (BAM) gives a good solution for measuring the mass concentration of atmospheric particles(PM10 and PM2.5). To determine particular matters (PM) concentration, a ratio of the number of detected beta-ray intensity passing through the clean filter and the dust-sampled filter is used. These intensity data measured in air pollution monitoring such as PM10 and PM2.5 usually contained the additive noise(thermal noise, power supply noise and etc.). Therefore, the estimation performance of mass concentration can be deteriorated by these noises. In this paper, we present a new noise reduction method that is essentially required to develope an automatic continuous PM monitoring system using beta-ray absorption method. By combining the block data averaging technique and curve fitting, in the proposed method, the additive noise can be reduced in the measured data. To evaluate the performance of the proposed method, computer simulations were performed with computer generated signals as the input.

Keywords

References

  1. J. T. Van Der Wai and L. H. J. M. Janssen, "Analysis of Spatial and Temporal Variations of PM10 Concentrations in The Netherlands using Kalman Filtering," Atmis. Environ., vol 34. pp. 3675-3687, 2000. https://doi.org/10.1016/S1352-2310(00)00085-6
  2. 환경부, 광화학 대기오염 및 미세먼지의 생성과정 규명과 저감태책 수립 : 미세먼지분야, 연구보고서, 환경부, 2003.
  3. W. K. Kang, Technology of Measuring Equipment for Air Pollution, Research Paper, KRISS, 1999.
  4. J. B. Wedding and M. A. Weigand, "An Automatic Particle Sampler with Beta Gauging," Jour. of the Air Waste Manage. Assoc., vol43, no, 4, pp. 475-479, 1993.
  5. FH62C14 Instruction Manual, Thermo, 2007.
  6. K. I. Hoi, K. V. Yuen, and K. M. Mok, "Optimizing The Performance of Kalman Filters Based Statistical Time-Varying Air Quality Models," Jour. of Gloval NEST, vol. 12, no. 1, pp. 27-39, 2010.
  7. I. Ionel and F. Popescu, "Methods for Online Monitoring of Air Pollution Concentaration," Air Quality, DOI:10.5772/9754, 2010.
  8. A. V. Oppenheim and R. W. Schafer, Discrete-Time Signal Processing 3rd Ed., Prentice-Hall, 2009.
  9. J. W. Demmel, Applied Numerical Linear Algebra, SIAM Philadelphia, 1997.