Pipeline Break Detection Using Pressure Transient Monitoring
Publication: Journal of Water Resources Planning and Management
Volume 131, Issue 4
Abstract
Sudden pipe breaks occur in water transmission pipelines and distribution mains. The consequences of these breaks can be very expensive because of the service interruption, the cost of repair, and damage to surrounding property and infrastructure. The costs associated with the pipeline breaks can be reduced by minimizing the break detection and location time. This paper presents a new continuous monitoring approach for detecting and locating breaks in pipelines. A sudden pipe break creates a negative pressure wave that travels in both directions away from the break point and is reflected at the pipeline boundaries. Using the pressure data measured at one location along the pipeline, the timing of the initial and reflected transient waves induced by the break determines the location of the break. The magnitude of the transient wave provides an estimate of the break size. The continuous monitoring technique uses a modified two-sided cumulative sum (CUSUM) algorithm to detect abrupt break-induced changes in the pressure data. The adaptive tuning of CUSUM parameters is implemented to detect breaks of differing sizes and opening times. The continuous monitoring technique is verified by using results from both laboratory and field experiments and shows potential for detecting and locating sudden breaks in real pipelines.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The work presented in this paper was partially supported by a Royal Swedish Academy of Sciences grant and an Australian Research Council grant. The authors want to thank Mark Stephens for help in planning and running field tests and United Water International, Adelaide, Australia, for access to the Willunga network.
References
Babovic, V., Drecourt, J.-P., Keijzer, M., and Friss Hansen, P. (2002). “A data mining approach to modelling of water supply assets.” Urban Water, 4(4), 401–414.
Basseville, M., and Nikiforov, I. V. (1993). Detection of abrupt changes: Theory and applications, Prentice Hall, Englewood Cliffs, N.J.
Bergant, A., and Simpson, A. R. (1995). “Water hammer and column separation measurements in an experimental apparatus.” Research Rep. R128, School of Civil and Environmental Engineering, University of Adelaide, Australia.
Brunone, B. (1999). “Transient test-based technique for leak detection in outfall pipes.” J. Water Resour. Plan. Manage., 125(5), 302–306.
Emara-Shabaik, H. E., Khulief, Y. A. and Hussaini, I. (2002). “A non-linear multiple-model state estimation scheme for pipeline leak detection and isolation.” Proc., Inst. Mech. Eng. Part I: J. Syst. Control Eng., 216(6): 497–512.
Isermann, R. (1984). “Process fault detection based on modeling and estimation methods—a survey.” Automatica, 20(4), 387–404.
Jönsson, L., and Larson, M. (1992). “Leak detection through hydraulic transient analysis.” Pipeline systems, B. Coulbeck and E. Evans, eds., Kluwer Academic, Dordrecht, The Netherlands, 273–286.
Liou, J. C. P., and Tian, J. (1995). “Leak detection—transient flow simulation approaches.” J. Energy Resour. Technol., 117(3), 243–248.
Misiunas, D., Vítkovský, J. P., Olsson, G., Simpson, A. R., and Lambert, M. F. (2003). “Pipeline burst detection and location using a continuous monitoring technique.” Proc., International Conf. on Advances in Water Supply Management, CCWI, 15–17 September, Imperial College, London, 89–96.
Mukherjee, J., and Narasimhan, S. (1996). “Leak detection in networks of pipelines by generalized likelihood ratio method.” Ind. Eng. Chem. Res., 35(6), 1886–1893.
Page, E. S., (1954). “Continuous inspection schemes.” Biometrika, 41, 100–115.
Pelletier, G., Mailhot, A., and Villeneuve, J.-P. (2003). “Modeling water pipe breaks—three case studies.” J. Water Resour. Plan. Manage., 129(2), 115–123.
Rajtar, J. M., and Muthiah, R. (1997). “Pipeline leak detection system for oil and gas flowlines.” J. Manuf. Sci. Eng., 119(1), 105–109.
Schlattman, D. T. (1991). “Pressure analysis improves lines’ leak-detection capabilities.” Oil & Gas J., 89(52), 98–101.
Silva, R., Buiatta, C., Cruz, S., and Pereira, J. (1996). “Pressure wave behaviour and leak detection in pipelines.” Comput. Chem. Eng., 20, S491–S496.
Wang, G., Dong, D., and Fang, C. (1993). “Leak detection for transport pipelines based on autoregressive modeling.” IEEE Trans. Instrum. Meas., 42(1), 68–71.
Whaley, R. S., Nicholas, R. E., and Van Reet, J. (1992). A tutorial on software based leak detection methods, Pipeline Simulation Interest Group, Houston.
Wylie, E. B., and Streeter, V. L. (1993). Fluid transients in systems, Prentice Hall, Englewood Cliffs, N.J.
Zhang, J. 2001. “Statistical pipeline leak detection for all operating conditions.” Pipeline Gas J., 229(2), 42–45.
Information & Authors
Information
Published In
Copyright
© 2005 ASCE.
History
Received: Mar 2, 2004
Accepted: Nov 12, 2004
Published online: Jul 1, 2005
Published in print: Jul 2005
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.