Detection and sizing of extended partial blockages in pipelines by means of a stochastic successive linear estimator

Effective water system management depends upon knowledge of the current state of a water pipeline system network. For example, in many cases, partial blockages in a water pipeline system are a source of inefficiencies, and result in an increase of pumping costs. These anomalies must be detected and corrected as early as possible. In this study, an algorithm is developed for detecting blockages by means of pressure transient measurements and estimating the diameter distribution resulting from their formation. The algorithm is a stochastic successive linear estimator that provides statistically the best unbiased estimate of diameter distribution due to partial blockages and quantifies the uncertainty associated with these estimates. We first present the theoretical formulation of the algorithm and then test it with a numerical case study.

[1]  Silvia Meniconi,et al.  Water-hammer pressure waves interaction at cross-section changes in series in viscoelastic pipes , 2012 .

[2]  M. Ferrante,et al.  Detecting leaks in pressurised pipes by means of transients , 2001 .

[3]  Walter A. Illman,et al.  Steady-state hydraulic tomography in a laboratory aquifer with deterministic heterogeneity: Multi-method and multiscale validation of hydraulic conductivity tomograms , 2007 .

[4]  Silvia Meniconi,et al.  Portable pressure wave‐maker for leak detection and pipe system characterization , 2008 .

[5]  F. Massey The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[6]  Pedro J. Lee,et al.  Extended blockage detection in pipelines by using the system frequency response analysis , 2012 .

[7]  Bruno Brunone,et al.  Transient Test-Based Technique for Leak Detection in Outfall Pipes , 1999 .

[8]  Silvia Meniconi,et al.  Leak detection in branched pipe systems coupling wavelet analysis and a Lagrangian model. , 2009 .

[9]  Amandeep Sharma,et al.  Incoherent scattering of gamma photons for non-destructive tomographic inspection of pipeline. , 2010, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[10]  Angus R. Simpson,et al.  Discrete Blockage Detection in Pipelines Using the Frequency Response Diagram: Numerical Study , 2008 .

[11]  M. Ferrante,et al.  Small Amplitude Sharp Pressure Waves to Diagnose Pipe Systems , 2011 .

[12]  Ali Haghighi,et al.  A fuzzy approach for considering uncertainty in transient analysis of pipe networks , 2012 .

[13]  P. Kitanidis,et al.  An Application of the Geostatistical Approach to the Inverse Problem in Two-Dimensional Groundwater Modeling , 1984 .

[14]  R. W. Andrews,et al.  Sensitivity Analysis for Steady State Groundwater Flow Using Adjoint Operators , 1985 .

[15]  S. L. Scott,et al.  Evaluation of the Backpressure Technique for Blockage Detection in Gas Flowlines , 1998 .

[16]  John P. Vítkovský,et al.  Discussion of “Detection of Partial Blockage in Single Pipelines” by P. K. Mohapatra, M. H. Chaudhry, A. A. Kassem, and J. Moloo , 2008 .

[17]  E. Benjamin Wylie,et al.  Fluid Transients in Systems , 1993 .

[18]  J. A. Vargas-Guzmán,et al.  The successive linear estimator: a revisit , 2002 .

[19]  Tim Ellis,et al.  A semi-autonomous sewer surveillance and inspection vehicle , 1996, Proceedings of Conference on Intelligent Vehicles.

[20]  S. L. Scott,et al.  Flow Testing Methods to Detect and Characterize Partial Blockages in Looped Subsea Flowlines , 1999 .

[21]  T.-C. Jim Yeh,et al.  A Geostatistical Inverse Method for Variably Saturated Flow in the Vadose Zone , 1995 .

[22]  Junfeng Zhu,et al.  Comparison of aquifer characterization approaches through steady state groundwater model validation: A controlled laboratory sandbox study , 2010 .

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

[24]  Silvia Meniconi,et al.  Transient tests for locating and sizing illegal branches in pipe systems , 2011 .

[25]  T. Yeh,et al.  Hydraulic tomography: Development of a new aquifer test method , 2000 .

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

[27]  M. Chaudhry,et al.  Detection of Partial Blockage in Single Pipelines , 2006 .

[28]  Silvia Meniconi,et al.  Discussion of “Detection of Partial Blockage in Single Pipelines” by P. K. Mohapatra, M. H. Chaudhry, A. A. Kassem, and J. Moloo , 2008 .

[29]  Bruno Brunone,et al.  Pipe system diagnosis and leak detection by unsteady-state tests. 1. Harmonic analysis , 2003 .

[30]  E. G. Vomvoris,et al.  A geostatistical approach to the inverse problem in groundwater modeling (steady state) and one‐dimensional simulations , 1983 .

[31]  Zoran Kapelan,et al.  A fast approach for multiobjective design of water distribution networks under demand uncertainty , 2011 .

[32]  Michael D. Dettinger,et al.  First order analysis of uncertainty in numerical models of groundwater flow part: 1. Mathematical development , 1981 .

[33]  Minghui Jin,et al.  AN ITERATIVE STOCHASTIC INVERSE METHOD: CONDITIONAL EFFECTIVE TRANSMISSIVITY AND HYDRAULIC HEAD FIELDS , 1995 .

[34]  Silvia Meniconi,et al.  In-Line Pipe Device Checking by Short-Period Analysis of Transient Tests , 2011 .

[35]  Zoran S. Kapelan,et al.  A hybrid inverse transient model for leakage detection and roughness calibration in pipe networks , 2003 .

[36]  Tian-Chyi J. Yeh,et al.  Characterization of aquifer heterogeneity using transient hydraulic tomography , 2004 .

[37]  M. Lambert,et al.  Detection and Location of a Partial Blockage in a Pipeline Using Damping of Fluid Transients , 2005 .

[38]  T.-C. Jim Yeh,et al.  An iterative geostatistical inverse method for steady flow in the vadose zone , 1996 .

[39]  A. Hunt,et al.  Fluid properties determine flow line blockage potential , 1996 .

[40]  Silvia Meniconi,et al.  Fast Transients As a Tool for Partial Blockage Detection in Pipes: First Experimental Results , 2011 .

[41]  M. F K Pasha,et al.  Effect of parameter uncertainty on water quality predictions in distribution systems-case study , 2010 .