Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Noise Characteristic Analysis of X-Ray Fluorescence Spectrum

형광 X-선 스펙트럼의 잡음 특징 분석

  • Lee, Jae-Hwan (Div. of Engineering Electronic and Information, Chonbuk National University) ;
  • Chon, Sun-Il (Div. of Engineering Electronic and Information, Chonbuk National University) ;
  • Yang, Sang-Hoon (Div. of Engineering Electronic and Information, Chonbuk National University) ;
  • Park, Dong-Sun (IT Convergence Research Center, Chonbuk National University)
  • 이재환 (전북대학교 전자정보공학부) ;
  • 천선일 (전북대학교 전자정보공학부) ;
  • 양상훈 (전북대학교 전자정보공학부) ;
  • 박동선 (전북대학교 IT융합연구센터)
  • Received : 2012.04.30
  • Accepted : 2012.05.10
  • Published : 2012.05.31
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Abstract

X-ray fluorescence spectrum analysis method can be applied in many areas, including concentration analysis of RoHS elements and heavy metals etc. and we can get analysis results in a relatively short time. Because X-ray fluorescence spectrum has noises and several artifacts that lowers the accuracy of the analysis. This paper analyzes the characteristics of the noise of the X-ray fluorescence spectrum to increase the accuracy of analysis. X-ray fluorescence spectrum have the characteristics of shot noise (Poisson noise), so the noise size is relatively large in the small signal portion and the noise the size is relatively small in the large part of the signal. Existing methods of analysis and to remove noises is a method for general purposes algorithm. Since these algorithm does not reflect these noise characteristics, we get distorted analysis result. We can design efficient noise remove algorithm based on the accurate noise analysis method, and we expect high accuracy results of the elemental concentration analysis result.

형광 X-선 스펙트럼을 분석 방법은 RoHS 성분 및 중금속 함량 분석 등 여러 분야에 응용이 가능하며 비교적 빠른 시간 안에 함량 분석 결과를 얻을 수 있다. 형광 X-선 스펙트럼에는 잡음 및 여러 요인이 포함되어 있어 분석 정확도를 떨어뜨린다. 본 논문에서는 여러 요인 중 잡음의 특징을 분석하여 형광 X-선 스펙트럼 분석의 정확도를 높이고자 한다. 형광 X-선 스펙트럼은 산탄잡음(푸아송 잡음)의 특징을 가지고 있으며, 따라서 작은 신호에서는 잡음의 크기가 상대적으로 크고, 큰 신호에서는 잡음의 크기가 상대적으로 작은 특징을 가지고 있다. 기존에 잡음을 분석하고 제거하는 방법 및 알고리즘은 이러한 특징을 반영하지 않은 일반적인 목적으로 사용되는 방법으로 일반적인 알고리즘을 사용하여 잡음을 제거하게 되면 왜곡된 결과를 얻게 된다. 정확한 잡음 분석을 기반으로 효율적인 잡음 제거 알고리즘을 설계할 수 있고, 또한 높은 정확도의 원소 함량 분석 결과를 기대할 수 있다.

Keywords

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