Leak Detection and Localization through Demand Components Calibration

AbstractSuccess in the application of any model-based methodology (e.g., design, control, supervision) highly depends on the availability of a well-calibrated model. The calibration of water distribution networks needs to be performed online due to the continuous evolution of demands. During the calibration process, background leakages or bursts can be unintentionally incorporated to the demand model and treated as a system evolution (change in demands). This work proposes a leak-detection and localization approach to be coupled with a calibration methodology that identifies geographically distributed parameters. The approach proposed consists in comparing the calibrated parameters with their historical values to assess if changes in these parameters are caused by a system evolution or by the effect of leakage. The geographical distribution allows unexpected behavior of the calibrated parameters (e.g., abrupt changes, trends, etc.) to be associated with a specific zone in the network. The performance of t...

[1]  Ian F. C. Smith,et al.  Model falsification diagnosis and sensor placement for leak detection in pressurized pipe networks , 2013, Adv. Eng. Informatics.

[3]  Zoran Kapelan,et al.  Quo vadis water distribution model calibration? , 2009 .

[4]  Joby Boxall,et al.  Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows , 2010 .

[5]  Gerard Sanz,et al.  Sensitivity Analysis for Sampling Design and Demand Calibration in Water Distribution Networks Using the Singular Value Decomposition , 2015 .

[6]  Zoran Kapelan,et al.  An assessment of the application of inverse transient analysis for leak detection: Part II – Collection and application of experimental data , 2003 .

[7]  Orazio Giustolisi,et al.  Demand Components in Water Distribution Network Analysis , 2012 .

[8]  Irp India Enhancing Analog to Digital Converter Resolution Using Oversampling Technique , 2014 .

[9]  K Sridharan,et al.  Inverse transient analysis in pipe networks , 1996 .

[10]  Zoran Kapelan,et al.  Automated Detection of Pipe Bursts and Other Events in Water Distribution Systems , 2014 .

[11]  Bryan W. Karney,et al.  A selective literature review of transient-based leak detection methods , 2009 .

[12]  Zheng Yi Wu,et al.  Pressure-dependent leak detection model and its application to a district water system , 2010 .

[13]  F. J. Arregui,et al.  Burst Detection in Water Networks Using Principal Component Analysis , 2012 .

[14]  Johannes Hugenschmidt,et al.  The inspection of retaining walls using GPR , 2009 .

[15]  Vicenç Puig,et al.  Methodology for leakage isolation using pressure sensitivity analysis in water distribution networks , 2011 .

[16]  Zheng Yi Wu,et al.  WATER LOSS DETECTION VIA GENETIC ALGORITHM OPTIMIZATION-BASED MODEL CALIBRATION , 2008 .

[17]  M. Taylor,et al.  A Selective Literature Review , 1992 .

[18]  Yi Wu Zheng,et al.  Optimization model for identifying unknown valve statuses and settings , 2012 .

[19]  Zoran Kapelan,et al.  Geostatistical techniques for approximate location of pipe burst events in water distribution systems , 2013 .

[20]  Fatiha Nejjari,et al.  Leak Localization in Water Networks: A Model-Based Methodology Using Pressure Sensors Applied to a Real Network in Barcelona [Applications of Control] , 2014, IEEE Control Systems.

[21]  Zoran Kapelan,et al.  A review of methods for leakage management in pipe networks , 2010 .

[22]  Sanghyun Kim Extensive Development of Leak Detection Algorithm by Impulse Response Method , 2005 .

[23]  Richard Mounce,et al.  Novelty detection for time series data analysis in water distribution systems using support vector machines , 2011 .

[24]  Zoran Kapelan,et al.  Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation , 2014 .

[25]  Frédéric Taillade,et al.  Truly Distributed Optical Fiber Sensors for Structural Health Monitoring: From the Telecommunication Optical Fiber Drawling Tower to Water Leakage Detection in Dikes and Concrete Structure Strain Monitoring , 2010 .

[26]  Joby Boxall,et al.  FIELD VALIDATION OF 'OPTIMAL' INSTRUMENTATION METHODOLOGY FOR BURST/LEAK DETECTION AND LOCATION , 2011 .

[27]  Kevin E Lansey,et al.  Effect of uncertainty on water distribution system model design decisions , 2009 .

[28]  K. Lansey,et al.  Demand and Roughness Estimation in Water Distribution Systems , 2011 .

[29]  Angus R. Simpson,et al.  Leak Detection and Calibration Using Transients and Genetic Algorithms , 2000 .

[30]  Thomas M. Walski,et al.  What Does it Take to Make Automated Calibration Find Closed Valves and Leaks , 2014 .

[31]  C. T. Haan,et al.  Calibration assessment and data collection for water distribution networks , 2001 .

[32]  Avi Ostfeld,et al.  Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions , 2014, Environ. Model. Softw..