Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received November 17, 2017; final manuscript received April 19, 2018; published online July 3, 2018. Assoc. Editor: John Michopoulos.
In most city water distribution systems, a considerable amount of water is lost because of leaks occurring in pipes. Moreover, an unobservable fluid leakage fault that may occur in a hazardous industrial system, such as nuclear power plant cooling process or chemical waste disposal, can cause both environmental and economical disasters. This situation generates crucial interest for industry and academia due to the financial cost related with public health risks, environmental responsibility, and energy efficiency. In this paper, to find a reliable and economic solution for this problem, adaptive neuro fuzzy inference system (ANFIS) method which consists of backpropagation and least-squares learning algorithms is proposed for estimating leakage locations in a complex water distribution system. The hybrid algorithm is trained with acceleration, pressure, and flow rate data measured through the sensors located on some specific points of the complex water distribution system. The effectiveness of the proposed method is discussed comparing the results with the current methods popularly used in this area.
Greyvenstein, B. , and van Zyl, J. E. , 2005, " An Experimental Investigation Into the Pressure-Leakage Relationship of Some Failed Water Pipes," Leakage 2005 Conference, Halifax, NS, Canada.
Stenberg, R. , 1982, " Leak Detection in Water Supply Systems," The Swedish Water and Waste Water Works Association, Stockholm, Sweden.
Thornton, J. , 2002, Water Loss Control Manual, McGraw-Hill, New York.
Farley, M. , and Trow, S. , 2003, Losses in Water Distribution Networks, IWA Publishing, London.
Pilcher, R. , Hamilton, S. , Chapman, H. , Ristovski, B. , and Strapely, S. , 2007, " Leak Location and Repair Guidance Notes," International Water Association—Water Loss Task Forces: Specialist Group Efficient Operation and Management, Bucharest, Romania, pp. 12–18.
Puust, R. , 2007, " Probabilistic Leak Detection in Pipe Networks Using the SCEM-UA," Ph.D. thesis, Tallinn University of Technology, Tallinn, Estonia.
Covas, D. , Ramos, H. , Lopes, N. , and Almeida, A. B. , 2006, " Water Pipe System Diagnosis by Transient Pressure Signals," Eighth Annual Water Distribution Systems Analysis Symposium, Cincinnati, OH, Aug. 27–30, pp. 1–19.
Araujo, L. S. , Ramos, H. M. , and Coelho, S. T. , 2003, " Estimation of Distributed Pressure-Dependent Leakage and Consumer Demand in Water Supply Networks," International Conference on Advances in Water Supply Management, London, Sept. 15–17.
Garcia, V. J. , Cabrera, E. , and Cabrera , E., Jr. , 2006, " The Minimum Night Flow Method Revisited," Eighth Annual Water Distribution Systems Analysis Symposium, Cincinnati, OH, Aug. 27–30, pp. 1–18.
AWWA, 1987, A Technical/Economic Overview. Leaks in Water Distribution Systems, American Water Works Association, Denver, CO.
O'Connor, K. M. , and Dowding, C. H. , 1999, GeoMeasurements by Pulsing TDR Cables and Probes, CRC Press, Boca Raton, FL.
Kupfer, K. , 2005, Electromagnetic Aquametry: Electromagnetic Wave Interaction With Water and Moist Substances, Springer-Verlag, New York.
Okhovvat, M. , and Fallahi, R. , 2006, " Measurements of Antenna Reflection Coefficients in Time Domain," IEEE International Conference Mathematical Methods in Electromagnetic Theory, Kharkiv, Ukraine, June 26–29, pp. 328–330.
Sanz, G. , Pérez, R. , and Escobet, A. , 2012, " Leakage Localization in Water Networks Using Fuzzy Logic," 20th Mediterranean Conference on in Control & Automation (MED), Barcelona, Spain, July 3–6, pp. 646–651.
Moczulski, W. , Wyczółkowski, R. , Ciupke, K. , Przystałka, P. , Tomasik, P. , and Wachla, D. , 2016, " A Methodology of Leakage Detection and Location in Water Distribution Networks—The Case Study," Third Conference on Control and Fault-Tolerant Systems (SysTol), Barcelona, Spain, Sept. 7–9, pp. 331–336.
De Rosa, C. T. , Fay, M. , Keith, L. S. , Mumtaz, M. M. , Pohl, H. R. , Hatcher, M. T. , Hicks, H. E. , Holler, J. , Ruiz, P. , and Johnson, B. L. , 2017, " Hazardous Wastes A2—Quah, Stella R," International Encyclopedia of Public Health, 2nd ed., Academic Press, Oxford, UK, pp. 358–370.
Twort, A. C. , Ratnayaka, D. D. , and Brandt, M. J. , 2017, " Chapter 5—Dams and Reservoirs," Twort's Water Supply, 7th ed., Butterworth-Heinemann, Boston, MA, pp. 159–204.
Yalçın B, Demir C, Gökçe M, Koyun A. Water Leakage Detection for Complex Pipe Systems Using Hybrid Learning Algorithm Based on ANFIS Method. ASME. J. Comput. Inf. Sci. Eng. 2018;18(4):041004-041004-10. doi:10.1115/1.4040130.