Probabilistic Failure Prediction for Deteriorating Pipelines: Nonparametric Approach
Publication: Journal of Performance of Constructed Facilities
Volume 22, Issue 1
Abstract
Component failures in water distribution systems are usually predicted by parametric models where the model parameters are determined by projecting the past failure rates of the component to the future. This paper shows that in such techniques, failures are implicitly assumed to be stationary random processes. However, due to the nonstationary nature of some influencing factors, this assumption may lead to inaccurate predictions. A new nonparametric technique is developed for failure prediction of classes of pipes considering this nonstationary process. The presented technique uses limited data that are typical to the databases of water distribution systems. In this method, maximum likelihood estimates of the probability of future failures are calculated and used, both to predict the number of failures occurring within a specified period of time in future, and to provide some lower and upper bounds (confidence intervals) for the estimations. This technique is applied to predict the failures of water pipes in western suburbs of Melbourne. Results of the predictions are compared with the empirical results from a failure record. Deviation of these predictions from empirical measures in terms of both rejection rates and mean-square errors of predictions are acceptable.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This research was supported by City West Water Company Pty Ltd., Victoria, Australia.
References
Andreou, S. A., et al. (1987). “A new methodology for modelling break failure patterns in deteriorating water distribution systems: Theory.” Adv. Water Resour., 10(1), 2–10.
Barraza, N. R., Cernuschi-Frías, B., and Cernuschi, F. (1995). “A probabilistic model for grouped events analysis.” Proc., 1995 IEEE Int. Conf. Systems, Man and Cybernetics, Vancouver, B.C., Canada, Vol. 4, 3386–3390.
Barraza, N. R., Cernuschi-Frías, B., and Cernuschi, F. (1996). “Applications and extensions of the chains-of-rare-events model.” IEEE Trans. Reliab., 45, 417–421.
Barraza, N. R., Pfefferman, J. D., Cernuschi-Frías, B., and Cernuschi, F. (2000). “An application of the chains-of-rare-events model to software development failure prediction.” Proc., 5th Int. Conf. Reliable Software Technologies, Lecture Notes in Computer Science, Vol. 1845, H. B. Keller and E. Plödereder, eds., Springer, New York, 185–195.
Cernuschi, F., and Castagnetto, L. (1946). “Chains of rare events.” Ann. Math. Stat., 17, 53–61.
Clark, R. M., and Goodrich, J. A. (1988). “Developing a data base on infrastructure needs.” J. Am. Water Works Assoc., 81(7), 81–87.
Crowder, M. J., et al. (1994). “Statistical analysis of reliability data.” Probability distribution in reliability, Chapman & Hall, London.
Dehghan, A., and McManus, K. J. (2005). “Improved estimation of water pipes reliability for urban water supply systems.” Proc., 1st Int. Conf. on Structural Condition Assessment, Monitoring and Improvement, Perth, W. Australia.
Dehghan, A., McManus, K. J., and Gad, E. (2005). “Statistical analysis of structural failures of water pipes in a case study.” J. ICE of Water Management, submission accepted, ⟨http://opax.swin.edu.au/~adehghan/ICE.pdf⟩.
Goel, A. L., and Okumoto, K. (1979). “Time-dependent error-detection rate model for software reliability and other performance measures.” IEEE Trans. Reliab., 28, 206–211.
Goulter, I. C., and Kazemi, A. (1988). “Spatial and temporal groupings of water main pipe breakage in Winnipeg.” Can. J. Civ. Eng., 15(1), 91–97.
Gustafson, J. M., and Clancy, D. V. (1999). “Modeling the occurrence of breaks in cast iron water mains using methods of survival analysis.” Proc., AWWA Annual Conf., American Water Works Association, Denver.
Hossain, S. A., and Dahiya, R. C. (1993). “Estimating the parameters of a nonhomogeneous Poisson-process model for software reliability.” IEEE Trans. Reliab., 42, 604–612.
Karaa, F. A., and Marks, D. H. (1990). “Performance of water distribution networks: Integrated approach.” J. Perform. Constr. Facil., 4(1), 51–67.
Kimber, A. C. (1995). “A Weibull-based score test for heterogeneity.” Lifetime Data Anal, 2(1), 63–71.
Kleiner, Y., and Rajani, B. (2001). “Comprehensive review of structural deterioration of water mains: Statistical models.” Urban Water, 3(3), 131–150.
Kleiner, Y., and Rajani, B. (2002). “Forecasting variations and trends in water-main breaks.” J. Infrastruct. Syst., 8(4), 122–131.
Kleiner, Y., and Rajani, B. (2003). “Water main assets: From deterioration to renewal.” Proc., AWWA Annual Conf. and Exposition—Catch the Wave, Anaheim, Calif., June 15–19, 1–12.
Leighton, T. F., and Rivest, R. L. (1986). “Estimating a probability using finite memory.” IEEE Trans. Inf. Theory, 32(6), 733–742.
Lyu, M. R. (1996). “Handbook of software reliability engineering.” Review of reliability theory, analytical techniques, Y. K. Malaiya and P. K. Srimani, eds., McGraw-Hill, New York, 748–750.
Miller, A. M. B. (1980). “A study of the Musa reliability model.” MS thesis, Univ. of Maryland, College Park, Md.
Musa, J. D. (1980). “The measurement and management of software reliability.” IEEE Trans. Software Eng., 68(9), 1131–1143.
Musa, J. D., Iannino, A., and Okumoto, K. (1987). Software reliability: Measurement, prediction, application, McGraw-Hill, New York, 223–241.
O’Day, D. K., et al. (1980). “Aging urban water systems: A computerized case study.” Public Works, 111(8), 61–64.
Rajani, B., and Tesfamariam, S. (2005). “Estimating time to failure of aging cast iron water mains under uncertainties.” Proc., Water Industry—Water Management for the 21st Century, Univ. of Exeter, U.K., Sept. 5–7, 1–7.
Righetti, B. (2001), “Cast iron condition assessment study.” Internal Rep. Neural Connection, City West Water, Melbourne, Australia.
Sahinoglu, M. (1992). “Compound-Poisson software reliability model.” IEEE Trans. Software Eng., 18, 624–630.
Shamir, U., and Howard, C. D. (1979). “An analytic approach to scheduling pipe replacement.” J. AWWA, 71(5), 248–258.
Stark, H. (1994). Probability, random processes, and estimation theory for engineers, 2nd Ed., Prentice-Hall, Englewood Cliffs, N.J.
Sukert, A. N. (1976). “A software reliability modeling study.” Technical Rep. No. RADC-TR-76-247, Rome Air Development Center, Rome.
Sukert, A. N. (1979). “Empirical validation of three error prediction models.” IEEE Trans. Reliab., 28, 199–205.
Tesfamariam, S., et al. (2006). “Possibilistic approach for consideration of uncertainties to estimate structural capacity of aging cast iron water mains.” Can. J. Civ. Eng., 33, 1050–1064.
Wood, A. (1996a). “Predicting software reliability.” IEEE Comput. Sci. Eng., 29, 69–77.
Wood, A. (1996b). “Software reliability growth models.” Rep. No. 96.1, Tandem Tech., Germany.
Water Service Association of Australia (WSAA). (1999). “WSAA facts ’99.” Melbourne, Australia.
Information & Authors
Information
Published In
Copyright
© 2008 ASCE.
History
Received: Sep 12, 2006
Accepted: Jun 19, 2007
Published online: Feb 1, 2008
Published in print: Feb 2008
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.