The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Noise Reduction Algorithm For The Detection of Fine Ion Signals in Residual Gas Analyzer

잔류가스분석기의 질량 스펙트럼 검출 성능 향상을 위한 잡음제거 알고리즘

  • Heo, Gyeongyong (Dept. of Electronic Engineering, Dongeui University) ;
  • Choi, Hun (Dept. of Electronic Engineering, Dongeui University)
  • Received : 2018.10.01
  • Accepted : 2018.12.03
  • Published : 2019.01.01
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Abstract

This paper proposes a method to improve the mass spectral detection performance of the residual gas analyzer. By improving the mode estimation method for setting the threshold value and improving the additive noise elimination method, it is possible to detect mass spectrums having low peak values of the threshold level difficult to distinguish from noise. Ion signal blocks for each mass index with noise removed by the improved method are effective for eliminating invalid ion signals based on the linear and quadratic fittings. The mass spectrum can be obtained from the quadratic fitted curves for the reconstructed ion signal block using only the valid ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed method, computer simulations were performed using real ion signals obtained from the residual gas analysis system under development. The simulation results show that the proposed method is valid.

Keywords

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그림 1 개발 중인 잔류가스분석기 구성도 Fig. 1 Configuration of residual gas analyzer under development

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그림 2 이상적인 질량 스펙트럼과 잡음의 1차 및 2차 피팅 특성 Fig. 2 Linear and quadratic fitting characteristics for ideal mass spectrum and noise

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그림 3 입력으로 사용한 이온신호 (a) SF6, (b) 잔류가스 Fig. 3 Ion signals as input (a) SF6, (b) residual gas

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그림 4 SF6에 대한 전처리 잡음제거 결과 (a) 추정한 최빈값으로 설정한 임계값, (b) 기존 알고리즘의 결과, (c) 제안한 알고리즘의 결과 Fig. 4 Results of pre-denoising processing for SF6 (a) threshold value set as the estimated mode (b) result of the conventional algorithm, (c) result of the proposed algorithm

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그림 5 잔류가스에 대한 전처리 잡음제거 결과 (a) 추정한 최빈값으로 설정한 임계값, (b) 기존 알고리즘의 결과, (c) 제안한 알고리즘의 결과 Fig. 5 Results of pre-denoising processing for residual gas (a) threshold value set as the estimated mode (b) result of the conventional algorithm, (c) result of the proposed algorithm

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그림 6 SF6 입력에 대한 기존 알고리즘과 제안한 알고리즘의 최종 질량 스펙트럼 검출 성능 비교 (a) 취득 이온신호, (b) 기존 알고리즘의 결과, (c) 제안한 알고리즘의 결과 Fig. 6 Comparison of detection performance of the final mass spectrum of the conventional algorithm and the proposed algorithm for the SF6 (a) measured ion signals, (b) result of the conventional algorithm, (c) result of the proposed algorithm

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그림 7 잔류가스 입력에 대한 기존 알고리즘과 제안한 알고리즘의 최종 질량 스펙트럼 검출 성능 비교 (a) 취득 이온 신호, (b) 기존 알고리즘의 결과, (c) 제안한 알고리즘의 결과 Fig. 7 Comparison of detection performance of the final mass spectrum of the conventional algorithm and the proposed algorithm for the residual gas (a) measured ion signals, (b) result of the conventional algorithm, (c) result of the proposed algorithm

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