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Research Papers: Techniques and Procedures

Calibration Zone for the Parameters of the Differential Evolution Algorithm and Its Application to a Real Burst Location Problem

[+] Author and Article Information
A. Pérez-González

Center of Research and Advanced Studies
of the National Polytechnic Institute,
Guadalajara Campus Av. del Bosque 1145,
El Bajio,
Zapopan, Jalisco 45019, Mexico
e-mail: aperez@gdl.cinvestav.mx

A. Badillo-Olvera

Center of Research and Advanced Studies
of the National Polytechnic Institute,
Guadalajara Campus Av. del Bosque 1145,
El Bajio,
Zapopan, Jalisco 45019, Mexico
e-mail: ambadillo@gdl.cinvestav.mx

O. Begovich

Center of Research and Advanced Studies
of the National Polytechnic Institute,
Guadalajara Campus Av. del Bosque 1145,
El Bajio,
Zapopan, Jalisco 45019, Mexico
e-mail: obegovi@gdl.cinvestav.mx

J. Ruíz-León

Center of Research and Advanced Studies
of the National Polytechnic Institute,
Guadalajara Campus Av. del Bosque 1145,
El Bajio,
Zapopan, Jalisco 45019, Mexico
e-mail: jruiz@gdl.cinvestav.mx

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received October 24, 2017; final manuscript received January 17, 2019; published online March 4, 2019. Assoc. Editor: Elias Balaras.

J. Fluids Eng 141(5), 051402 (Mar 04, 2019) (9 pages) Paper No: FE-17-1685; doi: 10.1115/1.4042749 History: Received October 24, 2017; Revised January 17, 2019

Numerical problems are usually solved using heuristic algorithms, due to their simplicity and easy understanding. Nevertheless, most of these methods have calibration parameters that do not count with selection premises oriented to obtain the best performance for the algorithm. This paper introduces an iterative technique that deals with this problem, searching for the calibration parameters that improve the Differential Evolution (DE) algorithm. The application of the proposed technique is illustrated on a real burst location problem in a pipeline prototype. The obtained results show the good performance of the methodology proposed for the burst location task, including the mapping of the calibration parameters that ameliorate the searching process.

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References

Holland, J. H. , 1970, “ Robust Algorithms for Adaptation Set in a General Formal Framework,” IEEE Symposium on Adaptive Processes Decision and Control, Austin, TX, Dec. 7–9, p. 175.
Schwefel, H. , 1965, “ Kybernetische Evolution Als Strategie Der Experimentellen Forschung in Die Strömungstechnik,” Diplomarbeit 233, TU Berlin, Technical Universite of Berlin, Germany.
Das, S. , and Suganthan, P. N. , 2011, “ Differential Evolution: A Survey of the State-of-the-Art,” IEEE Trans. Evol. Comput., 15(1), pp. 4–31. [CrossRef]
Liu, Y. , 2017, “ Adaptive Just-in-Time and Relevant Vector Machine Based Soft-Sensors With Adaptive Differential Evolution Algorithms for Parameter Optimization,” Chem. Eng. Sci., 172, pp. 571–584. [CrossRef]
Fanelli, M. , and Cabrera, E. , 2015, “ Detection of Abrupt Flow Discontinuities in Open-Surface Channels by Transient Analysis,” J. Hydraul. Eng., 142(1), p. 04015037. [CrossRef]
Pérez-González, A. , Begovich, O. , and Ruiz-León, J. , 2014, “ Modeling of a Greenhouse Prototype Using PSO Algorithm Based on a LabView TM Application,” 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Campeche, Mexico, Sept. 29–Oct. 3, pp. 1–6.
Clerc, M. , and Kennedy, J. , 2002, “ The Particle Swarm-Explosion, Stability, and Convergence in a Multidimensional Complex Space,” IEEE Trans. Evol. Comput., 6(1), pp. 58–73. [CrossRef]
Trelea, I. C. , 2003, “ The Particle Swarm Optimization Algorithm: Convergence Analysis and Parameter Selection,” Inf. Process. Lett., 85(6), pp. 317–325. [CrossRef]
Adedeji, K. B. , Hamam, Y. , Abe, B. T. , and Abu-Mahfouz, A. M. , 2017, “ Burst Leakage-Pressure Dependency in Water Piping Networks: Its Impact on Leak Openings,” IEEE AFRICON, Cape Town, South Africa, Sept. 18–20, pp. 1502–1507.
Ye, G. , and Fenner, R. A. , 2010, “ Kalman Filtering of Hydraulic Measurements for Burst Detection in Water Distribution Systems,” J. Pipeline Syst. Eng. Pract., 2(1), pp. 14–22. [CrossRef]
Misiunas, D. , Lambert, M. , Simpson, A. , and Olsson, G. , 2005, “ Burst Detection and Location in Water Distribution Networks,” Water Sci. Technol.: Water Supply, 5(3-4), pp. 71–80. [CrossRef]
Kowalczuk, Z. , and Gunawickrama, K. , 2004, “ Detecting and Locating Leaks in Transmission Pipelines,” Fault Diagnosis, Springer, Berlin, pp. 821–864.
Eiswirth, M. , and Burn, L. , 2001, “ New Methods for Defect Diagnosis of Water Pipelines,” Fourth International Conference in Water Pipeline Systems, York, UK, Mar. 28–30, pp. 137–150.
Chaudhry, M. H. , 2014, Applied Hydraulic Transients, Springer Science & Business Media, New York.
Delgado, M. , and Begovich, O. , 2017, “ A Comparison Between Leak Location Methods Based on the Negative Pressure Wave,” 14th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Mexico City, Mexico, Oct. 20–22, pp. 1–6.
Allen, M. , Prels, A. , Lqbal, M. , Srirangarajan, S. , Llm, H. B. , Glrod, L. , and Whittle, A. J. , 2011, “ Real-Time in-Network Distribution System Monitoring to Improve Operational Efficiency,” J.-Am. Water Works Assoc., 103(7), pp. 63–75. [CrossRef]
Martins, J. C. , and Seleghim, P., Jr , 2010, “ Assessment of the Performance of Acoustic and Mass Balance Methods for Leak Detection in Pipelines for Transporting Liquids,” ASME J. Fluids Eng., 132(1), p. 011401. [CrossRef]
Delgado-Aguiñaga, J. , Besancon, G. , Begovich, O. , and Carvajal, J. , 2016, “ Multi-Leak Diagnosis in Pipelines Based on Extended Kalman Filter,” Control Eng. Pract., 49, pp. 139–148. [CrossRef]
Verde, C. , 2005, “ Accommodation of Multi-Leak Location in a Pipeline,” Control Eng. Pract., 13(8), pp. 1071–1078. [CrossRef]
Verde, C. , and Torres, L. , 2017, Modeling and Monitoring of Pipelines and Networks: Advanced Tools for Automatic Monitoring and Supervision of Pipelines, Vol. 7, Springer, Cham, Switzerland.
Wylie, E. B. , Streeter, V. L. , and Suo, L. , 1993, Fluid Transients in Systems, Vol. 1, Prentice Hall, Englewood Cliffs, NJ.
Meniconi, S. , Brunone, B. , Ferrante, M. , Capponi, C. , Carrettini, C. , Chiesa, C. , Segalini, D. , and Lanfranchi, E. , 2015, “ Anomaly Pre-Localization in Distribution–Transmission Mains by Pump Trip: Preliminary Field Tests in the Milan Pipe System,” J. Hydroinformatics, 17(3), pp. 377–389. [CrossRef]
Soares, A. K. , Covas, D. I. , and Reis, L. F. , 2008, “ Analysis of PVC Pipe-Wall Viscoelasticity During Water Hammer,” J. Hydraul. Eng., 134(9), pp. 1389–1394. [CrossRef]
Meniconi, S. , Duan, H. , Brunone, B. , Ghidaoui, M. S. , Lee, P. , and Ferrante, M. , 2014, “ Further Developments in Rapidly Decelerating Turbulent Pipe Flow Modeling,” J. Hydraul. Eng., 140(7), p. 04014028. [CrossRef]
Axworthy, D. H. , Ghidaoui, M. S. , and McInnis, D. A. , 2000, “ Extended Thermodynamics Derivation of Energy Dissipation in Unsteady Pipe Flow,” J. Hydraul. Eng., 126(4), pp. 276–287. [CrossRef]
Brunone, B. , Golia, U. , and Greco, M. , 1995, “ Effects of Two-Dimensionality on Pipe Transients Modeling,” J. Hydraul. Eng., 121(12), pp. 906–912. [CrossRef]
Vardy, A. E. , and Brown, J. M. , 1995, “ Transient, Turbulent, Smooth Pipe Friction,” J. Hydraul. Res., 33(4), pp. 435–456. [CrossRef]
Prashanth Reddy, H. , Silva-Araya, W. F. , and Hanif Chaudhry, M. , 2011, “ Estimation of Decay Coefficients for Unsteady Friction for Instantaneous, Acceleration-Based Models,” J. Hydraul. Eng., 138(3), pp. 260–271. [CrossRef]
Zhao, M. , and Ghidaoui, M. , 2004, “ Review and Analysis of 1-D and 2-D Energy Dissipation Models for Transient Flows,” International Conference on Pressure Surges, Chester, UK, Mar. 24–26, pp. 477–492.
Duan, H. , Meniconi, S. , Lee, P. , Brunone, B. , and Ghidaoui, M. S. , 2017, “ Local and Integral Energy-Based Evaluation for the Unsteady Friction Relevance in Transient Pipe Flows,” J. Hydraul. Eng., 143(7), p. 04017015. [CrossRef]
Bergant, A. , Ross Simpson, A. , and Vìtkovsk, J. , 2001, “ Developments in Unsteady Pipe Flow Friction Modelling,” J. Hydraul. Res., 39(3), pp. 249–257. [CrossRef]
Pezzinga, G. , 2009, “ Local Balance Unsteady Friction Model,” J. Hydraul. Eng., 135(1), pp. 45–56. [CrossRef]
Vítkovsky`, J. P. , Bergant, A. , Simpson, A. R. , and Lambert, M. F. , 2006, “ Systematic Evaluation of One-Dimensional Unsteady Friction Models in Simple Pipelines,” J. Hydraul. Eng., 132(7), pp. 696–708. [CrossRef]
Vardy, A. , and Brown, J. , 2004, “ Transient Turbulent Friction in Fully Rough Pipe Flows,” J. Sound Vib., 270(1–2), pp. 233–257. [CrossRef]
Vítkovsky`, J. , Stephens, M. , Bergant, A. , Simpson, A. , and Lambert, M. , 2006, “ Numerical Error in Weighting Function-Based Unsteady Friction Models for Pipe Transients,” J. Hydraul. Eng., 132(7), pp. 709–721. [CrossRef]
Zarzycki, Z. , 2000, “ On Weighting Function for Wall Shear Stress During Unsteady Turbulent Pipe Flow,” Eighth International Conference on Pressure Surges, The Hague, The Netherlands, pp. 529–543.
Dulhoste, J.-F. , Besançon, G. , Torres, L. , Begovich, O. , and Navarro, A. , 2011, “ About Friction Modeling for Observer-Based Leak Estimation in Pipelines,” 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, FL, Dec. 12–15, pp. 4413–4418.
Dulhoste, J. F. , Guillén, M. , Besançon, G. , and Santos, R. , 2017, “ One-Dimensional Modeling of Pipeline Transients,” Modeling and Monitoring of Pipelines and Networks, Springer, Cham, Switzerland, pp. 63–81.
Sotelo Avila, G. , 1991, Hidráulica General; Fundamentos, Limusa, Mexico city, Mexico.
Besançon, G. , 2017, “ Observer Tools for Pipeline Monitoring,” Modeling and Monitoring of Pipelines and Networks, Springer, Cham, Switzerland, pp. 83–97.
Navarro, A. , Begovich, O. , Sánchez, J. , and Besancon, G. , 2017, “ Real-Time Leak Isolation Based on State Estimation With Fitting Loss Coefficient Calibration in a Plastic Pipeline,” Asian J. Control, 19(1), pp. 255–265. [CrossRef]
Delgado-Aguiñaga, J. , Besançon, G. , and Begovich, O. , 2015, “ Leak Isolation Based on Extended Kalman Filter in a Plastic Pipeline Under Temperature Variations With Real-Data Validation,” 23th Mediterranean Conference on Control and Automation (MED), Torremolinos, Spain, June 16–19, pp. 316–321.
Badillo-Olvera, A. , Begovich, O. , and Peréz-González, A. , 2017, “ Leak Isolation in Pressurized Pipelines Using an Interpolation Function to Approximate the Fitting Losses,” Journal of Physics: Conference Series, Lille, France, p. 012012.
Storn, R. , and Price, K. , 1997, “ Differential Evolution—A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces,” J. Global Optim., 11(4), pp. 341–359. [CrossRef]
Price, K. , Storn, R. M. , and Lampinen, J. A. , 2006, Differential Evolution: A Practical Approach to Global Optimization, Springer Science & Business Media, Berlin.
Pérez-González, A. , Begovich, O. , and Ruiz-León, J. , 2016, “ Evolutive Extension: A Biological Approach to Heuristic Algorithms,” Latin American Conference on Automatic Control (XVII CLCA), Medellín, Colombia, pp. 373–378.

Figures

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Fig. 1

Flow rate before and after the leak occurrence

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Fig. 2

Pressure profile before and after the leak occurrence

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Fig. 3

Pipeline discretization scheme

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Fig. 5

Block diagram for the basic structure of evolutive algorithms

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Fig. 6

Flow rate and pressure head measurements with an emulated burst at valve 3

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Fig. 7

Calibration zone for calibration parameters of the DE algorithm in the BDI problem

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Fig. 8

Total mean square error of Gbest for each execution of the DE algorithm

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Fig. 9

Flow rate and pressure head measurements with an emulated burst at valve 1

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Fig. 10

Application of the CZ for the calibration parameters of the DE algorithm in the BDI problem

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Fig. 11

Total mean square error of Gbest for each execution of the DE algorithm (restricted to the CZ)

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