상하수도학회지 (Journal of Korean Society of Water and Wastewater)

  • 제37권6호
  • /
  • Pages.383-394
  • /
  • 2023
  • /
  • 1225-7672(pISSN)
  • /
  • 2287-822X(eISSN)
대한상하수도학회 (The Korean Society of Water and Wastewater)
권호 표지
DOI QR코드

DOI QR Code

상수관망 데이터 수집의 최적 빈도 결정을 위한 방법론적 접근

Methodology for determining optimal data sampling frequencies in water distribution systems

  • 김현준 (부산대학교 기계공학부) ;
  • 정은혜 (주식회사 플로워크연구소 연구개발팀) ;
  • 황경엽 (블루센(주) 연구개발실)
  • Hyunjun Kim (Department of Mechanical Engineering, Pusan National University) ;
  • Eunhye Jeong (Research and Development Department, FloWork Lab.) ;
  • Kyungyup Hwang (Technology Research Institute, BLUESEN Co. Ltd.)
  • 투고 : 2023.11.16
  • 심사 : 2023.12.05
  • 발행 : 2023.12.15
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Currently, there is no definitive regulation for the appropriate frequency of data sampling in water distribution networks, yet it plays a crucial role in the efficient operation of these systems. This study proposes a new methodology for determining the optimal frequency of data acquisition in water distribution networks. Based on the decomposition of signals using harmonic series, this methodology has been validated using actual data from water distribution networks. By analyzing 12 types of data collected from two points, it was demonstrated that utilizing the factors and cumulative periodograms of harmonic series enables similar accuracy at lower data acquisition frequencies compared to the original signals. Type your abstract here.

키워드

과제정보

이 연구는 2023년도 산업통상자원부 및 산업기술평가관리원(KEIT) 연구비 지원에 의한 연구임(20025188).

참고문헌

  1. Brunone, B., Ferrante, M. and Meniconi, S. (2008). Portable pressure wavemaker for leak detection and pipe system characterization, J. Am. Water Works Assn., 100, 108-116. https://doi.org/10.1002/j.1551-8833.2008.tb09607.x
  2. Covas, D. and Ramos, H. (2010). Case studies of leak detection and location in water pipe systems by inverse transient analysis, J. Water Resour. Plan. Manag., 136, 248-257. https://doi.org/10.1061/(ASCE)0733-9496(2010)136:2(248)
  3. Enriquez, L., Saldarriaga, J., Berardi, L., Laucelli, D. and Giustolisi, O. (2023). "Using artificial intelligence models to support water quality prediction in water distribution networks", International Conference on Hydroinformatics, 4-8 July, 2022, Bucharest, Romania, IOP Conference Series: Earth and Environmental Science.
  4. Kim, S.H. (2011). Holistic unsteady friction model for the laminar transient flow in pipeline systems, J. Hydrau.l Eng., 137, 1649-1658. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000471
  5. Kim, S.H., Zecchine, A. and Choi, R.W. (2014). Diagnosis of a pipeline system for transient flow in low Reynolds number with impedance method, J. Hydraul. Eng., 140, 04014063.
  6. Lee, K.H., Suh, J.C., Cha, H.J., Song, K.S. and Choi, J.M. (2013). Study on the sampling rate for the purpose of use in water distribution network data, J. Korean Soc. Water wastewater, 27, 233-239. https://doi.org/10.11001/jksww.2013.27.2.233
  7. Zhou, Y. (1996). Sampling frequency for monitoring the actual state of groundwater systems, J. Hydrol., 180, 301-318. https://doi.org/10.1016/0022-1694(95)02892-7