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Evaluation of Datum Unit for Diagnostics of Journal-Bearing Systems

저널베어링의 이상상태 진단을 위한 데이텀 효용성 평가

  • Jeon, Byungchul (Dept. of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.) ;
  • Jung, Joonha (Dept. of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.) ;
  • Youn, Byeng D. (Dept. of Mechanical and Aerospace Engineering, Seoul Nat'l Univ.) ;
  • Kim, Yeon-Whan (Power Generation Laboratory, KEPCO Research Institute) ;
  • Bae, Yong-Chae (Power Generation Laboratory, KEPCO Research Institute)
  • 전병철 (서울대학교 기계항공공학부) ;
  • 정준하 (서울대학교 기계항공공학부) ;
  • 윤병동 (서울대학교 기계항공공학부) ;
  • 김연환 (한국전력 전력연구원 발전연구소) ;
  • 배용채 (한국전력 전력연구원 발전연구소)
  • Received : 2014.11.24
  • Accepted : 2015.06.25
  • Published : 2015.08.01

Abstract

Journal bearings support rotors using fluid film between the rotor and the stator. Generally, journal bearings are used in large rotor systems such as turbines in a power plant, because even in high-speed and load conditions, journal bearing systems run in a stable condition. To enhance the reliability of journal-bearing systems, in this paper, we study health-diagnosis algorithms that are based on the supervised learning method. Specifically, this paper focused on defining the unit of features, while other previous papers have focused on defining various features of vibration signals. We evaluate the features of various lengths or units on the separable ability basis. From our results, we find that one cycle datum in the time-domain and 60 cycle datum in the frequency domain are the optimal datum units for real-time journal-bearing diagnosis systems.

저널베어링은 회전하는 축과 베어링 지지부 사이에 유막을 형성하여 회전체를 지지하는 구조물이며, 고속 및 고하중 조건에서도 안정적이기 때문에 발전소와 같은 대형 시스템에 널리 사용되고 있다. 본 연구에서는 저널베어링 시스템의 신뢰성을 확보하기 위한 감독학습 기반의 상태진단 알고리즘을 연구하였다. 기존에는 진동신호 특성인자들의 정의에 대한 연구가 주로 진행되었으나, 본 연구에서는 정의된 특성인자의 추출단위인 데이텀의 적용 기준에 대한 연구가 수행되었다. 데이텀의 효용성 평가를 통해 저널베어링 회전체 특성인자의 추출기준은 시간영역에서 1 회전, 주파수영역에서 60 회전 기준이 타당하다는 결론을 도출하였다.

Keywords

References

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