한국압력기기공학회 논문집 (Transactions of the Korean Society of Pressure Vessels and Piping)

한국압력기기공학회 (Korean Society of Pressure Vessels and Piping)
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배관내 압력변동 신호를 이용한 유량 추정 방법 연구

A Study on Flow Rate Estimation Using Pressure Fluctuation Signals in Pipe

  • 이정한 (한국원자력연구원) ;
  • 장대식 (한국원자력연구원) ;
  • 박진호 (한국원자력연구원)
  • Jeong Han Lee ;
  • Dae Sic Jang ;
  • Jin Ho Park
  • 투고 : 2023.11.17
  • 심사 : 2023.12.21
  • 발행 : 2023.12.30
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초록

In nuclear power plants, the flow rate information is a major indicator of the performance of rotating equipment such as pumps, and is a very important one required for facility operation and maintenance. To measure a flow rate, various types of methods have been developed and used. Among them, the differential pressure type using orifice and the direct doppler type using ultrasonic waves are the most commonly used. However, these flow rate measurement methods have limitations in installation, conditions and status of the measuring part, etc. To solve this problem, we have studied a new technique for measuring flow rate from scratch. In this paper, we have devised a technique to estimate the flow rate using an average moving velocity of large-scale eddy in turbulence that occurs in the piping flow field. The velocity of the large-scale eddy can be measured using the pressure fluctuation signals on the inner surface of the pipe. To estimate the flow rate, at first a cross-correlation function is applied to the two pressure fluctuation signals located at different positions in the down stream for calculating the time delay between the moving eddies. In order to validate the proposed flow rate estimation method, CFD analyses for the internal turbulence flow in pipe are conducted with a fixed flow condition, where the pressure fluctuation signals on the pipe inner surface are simulated. And then the average flow velocity of the large scale eddy is to be estimated. The estimated flow velocity is turned out to be similar to the fixed (known) flow rate.

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과제정보

이 논문은 2023년도 정부(산업통상자원부)의 재원으로 한국에너지기술평가원의 지원을 받아 수행된 연구임(20224B10100060, 회전설비 인공지능형 진동 감시 시스템 개발)

참고문헌

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