Journal of the Korean Vacuum Society (한국진공학회지)

The Korean Vacuum Society (한국진공학회)
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Study on Vacuum Pump Monitoring Using Adaptive Parameter Model

적응형 인자 모델을 이용한 개선된 진공펌프 상태진단에 관한 연구

  • Lee, Kyu-Ho (Engineering Research Institute, Department of Mechanical and Aerospace Engineering, Seoul National University) ;
  • Lee, Soo-Gab (Engineering Research Institute, Department of Mechanical and Aerospace Engineering, Seoul National University) ;
  • Lim, Jong-Yeon (Korea Research Institute of Standards and Science) ;
  • Cheung, Wan-Sup (Korea Research Institute of Standards and Science)
  • 이규호 (서울대학교 기계항공공학부, 공학연구소) ;
  • 이수갑 (서울대학교 기계항공공학부, 공학연구소) ;
  • 임종연 (한국표준과학연구원) ;
  • 정완섭 (한국표준과학연구원)
  • Received : 2010.12.27
  • Accepted : 2011.04.20
  • Published : 2011.05.30
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Abstract

This paper introduces statistical features observed from measured batch data from the multiple operation state variables of dry vacuum pumps running in the semiconductor processes. The amplitude distribution characteristics of such state variables as inlet pressures, supply currents of the booster and dry pumps, and exhaust pressures are shown to be divided into two or three distinctive regions. This observation gives an idea of using an adaptive parametric model (APM) chosen to describe their statistical features. This modelling, in comparison to the traditional dynamic time wrapping algorithm, is shown to provide superior performance in computation time and memory resources required in the preprocessing stage of sampled batch data for the diagnosis of running dry vacuum pumps. APM model-based batch data are demonstrated to be very appropriate for monitoring and diagnosing the running conditions of dry vacuum pumps.

본 논문에서는 건식 진공펌프에서 측정한 다중 변수로 구성된 배치데이터의 통계적인 특성을 소개한다. 흡입구 및 배출구 압력과 부스터/드라이 펌프의 소비전류와 같은 상태변수의 변위분포는 2개나 3개의 특정적인 구간으로 나뉘는 특성이 있다. 이런 관측을 통해 발견한 통계학적 특성을 나타내기 위해 적응형 인자 모델(APM)을 사용하였다. APM 모델기반의 배치 데이터는 건식 진공펌프의 상태를 진단하는데 적절함을 증명하였고, 이전의 동적 시간 왜곡 알고리즘과 비교하였을 때 계산시간 및 필요 메모리 면에서 효율적임을 확인하였다.

Keywords

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