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http://dx.doi.org/10.3741/JKWRA.2018.51.8.703

Data-driven event detection method for efficient management and recovery of water distribution system man-made disasters  

Jung, Donghwi (Department of Civil Engineering, Keimyung University)
Ahn, Jaehyun (Department of Civil & Architectural Engineering, Seokyeong University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.8, 2018 , pp. 703-711 More about this Journal
Abstract
Water distribution system (WDS) pipe bursts are caused from excessive pressure, pipe aging, and ground shift from temperature change and earthquake. Prompt detection of and response to the failure event help prevent large-scale service interruption and catastrophic sinkhole generation. To that end, this study proposes a improved Western Electric Company (WECO) method to improve the detection effectiveness and efficiency of the original WECO method. The original WECO method is an univariate Statistical Process Control (SPC) technique used for identifying any non-random patterns in system output data. The improved WECO method multiples a threshold modifier (w) to each threshold of WECO sub-rules in order to control the sensitivity of anomaly detection in a water distribution network of interest. The Austin network was used to demonstrated the proposed method in which normal random and abnormal pipe flow data were generated. The best w value was identified from a sensitivity analysis, and the impact of measurement frequency (dt = 5, 10, 15 min etc.) was also investigated. The proposed method was compared to the original WECO method with respect to detection probability, false alarm rate, and averaged detection time. Finally, this study provides a set of guidelines on the use of the WECO method for real-life WDS pipe burst detection.
Keywords
Water distribution systen (WDS); Event detection; Pipe burst; Disaster management; Disaster recovery;
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1 Jung, D., Kang, D., Liu, J., and Lansey, K. (2015). "Improving the rapidity of responses to pipe burst in water distribution systems: a comparison of statistical process control methods." Journal of Hydroinformatics, Vol. 17, No. 2, pp. 307-328.   DOI
2 Kang, B. M., and Hong, I. S. (2004). "A study on a remote leakage sensing system in waterworks network." The KIPS Transactions: Part D, Vol. 11, No. 6, pp. 1311-1318.
3 Kim, J. H., Lee, D. J., Bae, C. H., and Woo, H. M. (2009). "Technical application and analysis for reduction of water loss in water distribution systems." Proceedings Korea Water Resources Association Conference, KWRA, pp. 260-266.
4 Kim, S. W., Choi, D. Y., Bae, C. H., and Kim, J. (2013). "Leakage detection of water distribution system using adaptive Kalman filter. Journal of Korea Water Resources Association, Vol. 46, No. 10, pp. 969-976.   DOI
5 National Disaster Management Research Institute (2017). accessed 1 June 2018, .
6 Ministry of Environment (2010). Water distribution system standards.
7 Oh, H. C., Jo, Y. S., Hyun, S. Y., and Kim, S. Y. (2003). "A feasibility study on the detection of water leakage using a ground-penetrating radar." Journal of Korean Institute of Electromagnetic Engineering and Science, Vol. 14, No. 6, pp. 616-624.
8 Rossman, L. (2000). EPANet2 User's Manual. U.S. Environmental Protection Agency, Washington, DC.
9 Yoo, D. G., Jung, D., Kang, D., Kim, J. H., and Lansey, K. (2015). "Seismic hazard assessment model for urban water supply networks." Journal of Water Resources Planning and Management, Vol. 142, No. 2, 04015055.
10 Yoon, D. J., Jeong, J. C., and Lee, Y. S. (2003). "Leak detection of waterworks pipeline using acoustic emission and correlation method." Proceedings KSME Conference, KSME, pp. 84-89.
11 Hagos, M., Jung, D., and Lansey, K. E. (2016). "Optimal meter placement for pipe burst detection in water distribution systems." Journal of Hydroinformatics, Vol. 18, No. 4, pp. 741-756.   DOI
12 Jung, D., and Lansey, K. (2015). "Water distribution system burst detection using a nonlinear Kalman filter." Journal of Water Resources Planning and Management, No. 141, Vol. 5, 04014070.   DOI