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A Review on Different Pipeline Defect Detection Techniques

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Flow Modelling and Control in Pipeline Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 321))

Abstract

This chapter attempts to outline the pipeline failures and their impact on safety and environmental risks besides causing blockages and leaks in pipe networks. Furthermore, non-destructive testing techniques for detecting leakage and blockage are studied. They are visual detection approach, fluid odorant approach, mass balance approach, real-time transient model-based approach, pressure deviation approach, supervisory control and data acquisition system based on leakage identification approaches, pipeline hydrotest approach, magnetic and ultrasonic pipe detection approaches, acoustic emission inspection and monitoring system, wave warning system, pulse-echo flaw detector approach and acoustic wave reflectometry. Eventually, the stationary wavelet transform method is presented for structural health monitoring.

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References

  1. U.S Department of Transportation FAA.: Flight Standards Service-Aviation Maintenance Technical Handbook-Airframe, 2 (12 and 14) (2012). doi: FAA-H-8083-31

    Google Scholar 

  2. Folga, S.M.: Natural Gas Pipeline Technology Overview.: Argonne National Laboratory ANL/EVS/TM/08-5:1-12 (2007)

    Google Scholar 

  3. Chris, T., Saguna, A.: Pipeline Leak Science Series. 5th Tome 1st Fasc (2007)

    Google Scholar 

  4. Barker, M., Fessler, R.R., Biztek, R.: Pipeline and Hazardous Materials Safety Administration Office of Pipeline and Safety, Integrity Management Program, Pipeline Corrosion. Final Report, US Department of Transportation, Under Delivery Order DTRS56–02-D-70036 (2008)

    Google Scholar 

  5. Machell, J., Mounce, S., Boxall, J.B.: Online Modelling of Water Distribution Systems: A UK Case Study, Drinking Water Engineering and Science (2010)

    Google Scholar 

  6. Sider, A.: High-tech monitors often miss oil pipeline leaks. Wall Street J. (2014)

    Google Scholar 

  7. Warda, H.A., Adam, G., Rashad, A.B.: A practical implementation of pressure transient analysis in leak localization in pipelines. Int. Pipeline Conf. (2004). https://doi.org/10.1115/IPC2004-0551

    Article  Google Scholar 

  8. Baker, M., Fessler, R.R., Biztek, R.: Pipeline Corrosion. Final Report, U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration Office of Pipeline Safety. Integrity Management Program, Under Delivery Order (2008)

    Google Scholar 

  9. Willcox, M., Downes, G.: A Brief Description of NDT Techniques. Insight NDT Limited (2000–2003)

    Google Scholar 

  10. Duan, H.F., Lee, P.J.: Experimental investigation of wave scattering effect of pipe blockages on transient analysis. In: 16th Conference on Water Distribution System Analysis 891314-1320WDSA Science Direct (2014)

    Google Scholar 

  11. Lazhar, A., Hadj-Taieb, L., Hadj-Taieb, E.: Two leaks detection in viscoelastic pipeline systems by means of transient. J. Loss Prev. Process Ind. 26, 1341–1351 (2013)

    Article  Google Scholar 

  12. Duan, H.F., Lee, P., Ghidaoui, M.: Transient wave-blockage interaction in pressurized water pipelines. In: 12th International Conference on Computing and Control for the Water Industry, CCW12013 Science Direct, vol. 70, pp. 573–582 (2014)

    Google Scholar 

  13. Kaliatka, A., Vaisnoras, M., Valincius, M.: Modelling of valve induced water hammer phenomena in a district heating system. J. Comput. Fluids 94, 30–36 (2014)

    Article  MATH  Google Scholar 

  14. Riedelmeier, S., Becker, S., Schlucker, E.: Measurements of junction coupling during water hammer in piping systems. J. Fluids Struct. 48, 156–168 (2014)

    Article  Google Scholar 

  15. Tijsseling, A.S.: Water hammer with fluid-structure interaction in thick-walled pipes. Comput. Struct. 85, 844–851 (2007)

    Article  Google Scholar 

  16. Wang, R., Wang, Z., Wang, X., Yang, H., Sun, J.: Water hammer assessment techniques for water distribution systems. Procedia Eng. 70, 1717–1725 (2014)

    Article  Google Scholar 

  17. Delgado, J.N., Martins, N.M.C., Covas, D.I.C.: Uncertainties in hydraulic transient modelling in raising pipe systems. Laboratory case studies Science Direct Procedia Engineering, vol. 70, pp. 487–496 (2014)

    Google Scholar 

  18. Nayak, C.: Fault detection in fluid flowing pipes using acoustic method. Int. J. Appl. Eng. Res. 9(1), 23–28 (2014)

    Google Scholar 

  19. Sharp, D.B., Campbell, D.M.: Leak detection in pipes using acoustic pulse reflectometry. Acustica 83(3), 560–566 (1997)

    Google Scholar 

  20. Duan, W., Kiby, R., Prisutova, J., Horoshenkov, K.V.: On the use of power reflection ratio and phase change to determine the geometry of blockage in a pipe. J. Appl. Acoust. 87, 190–197 (2015)

    Article  Google Scholar 

  21. Hunaidi, O., Wang, A.: A new system for locating leaks in urban water distribution pipes. Int. J. Manage. Environ. Q. 17(4), 450–466 (2006)

    Google Scholar 

  22. Duan, H.F., Lee, P.J., Ghidaoui, M.S., Tuck, J.: Transient wave-blockage interaction and extended blockage detection in elastic water pipelines. J. Fluids Struct. 46, 2–16 (2014)

    Article  Google Scholar 

  23. Jafarian, A., Jafari, R.: Approximate solutions of dual fuzzy polynomials by feed-back neural networks. J. Soft Comput. Appl. 2012, 1–5 (2012)

    Google Scholar 

  24. Jafarian, A., Jafari, R.: An iterative method for solving fuzzy polynomials by fuzzy neural networks. In: 6th International Conference on Fuzzy Information and Engineering, Iran (2012)

    Google Scholar 

  25. Jafarian, A., Jafari, R.: Simulation and evaluation of fuzzy polynomials by feed-back neural networks. In: 6th International Conference on Fuzzy Information and Engineering, Iran (2012)

    Google Scholar 

  26. Jafarian, A., Jafari, R.: New iterative approach for solving fully fuzzy polynomials. Int. J. Fuzzy Math. Syst. 3 (1) (2013)

    Google Scholar 

  27. Jafarian, A., Jafari, R.: New method for solving fuzzy polynomials. Adv. Fuzzy Math. 8(1), 25–33 (2013)

    Google Scholar 

  28. Jafari, R., Yu, W.: Uncertainty nonlinear systems control with fuzzy equations. In: 2015 IEEE International Conference on Systems, Man, and Cybernetics, pp. 2885–2890. IEEE (2015)

    Google Scholar 

  29. Jafari, R., Yu, W.: Artificial neural network approach for solving strongly degenerate parabolic and burgers-fisher equations. In: 2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), pp. 1–6. IEEE (2015)

    Google Scholar 

  30. Jafari, R., Yu, W.: Fuzzy control for uncertainty nonlinear systems with dual fuzzy equations. J. Intell. Fuzzy Syst. 29(3), 1229–1240 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  31. Jafarian, A., Jafari, R., Golmankhaneh, A.K., Baleanu, D.: Solving fully fuzzy polynomials using feed-back neural networks. Int. J. Comput. Math. 92(4), 742–755 (2015)

    Article  MATH  Google Scholar 

  32. Jafari, R., Yu, W., Li, X.: Solving fuzzy differential equation with Bernstein neural networks. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016. vol 978-1-5090-1897-0/16/$31.00 ©2016 IEEE. 2016 IEEE International Conference on Systems, Man, and Cybernetics • SMC, pp. 1245–1250 (2016)

    Google Scholar 

  33. Jafarian, A., Jafari, R.: A new iterative approach based on artificial intelligence for solving dual fuzzy polynomials. In: 2nd International Conference on Technology-Engineering and Science (2016)

    Google Scholar 

  34. Jafarian, A., Jafari, R., Al Qurashi, M.M., Baleanu, D.: A novel computational approach to approximate fuzzy interpolation polynomials. SpringerPlus 5(1), 1428 (2016)

    Article  Google Scholar 

  35. Razvarz, S., Jafari, R.: Experimental study of Al2O3 nanofluids on the thermal efficiency of curved heat pipe at different tilt angle. In: 2nd International Conference on Technology-Engineering and Science (2016)

    Google Scholar 

  36. Jafari, R., Yu, W.: Fuzzy Modeling for Uncertainty Nonlinear Systems with Fuzzy Equations. Mathematical Problems in Engineering 2017 (2017) https://doi.org/10.1155/2017/8594738

  37. Jafari, R., Yu, W.: Uncertain nonlinear system control with fuzzy differential equations and Z-numbers. In: 2017 IEEE International Conference on Industrial Technology (ICIT), pp. 890–895. IEEE (2017)

    Google Scholar 

  38. Jafari, R., Yu, W., Li, X.: Fuzzy differential equations for nonlinear system modeling with Bernstein neural networks. IEEE Access 4, 9428–9436 (2017)

    Article  Google Scholar 

  39. Jafari, R., Yu, W., Li, X.: Numerical solution of fuzzy equations with Z-numbers using neural networks. Intell. Autom. Soft Comput., 1–7 (2017)

    Google Scholar 

  40. Razvarz, S., Jafari, R.: Intelligent techniques for photocatalytic removal of pollution in wastewater. J. Electr. Eng. 5(1), 321–328 (2017a)

    Google Scholar 

  41. Jafari, R., Razvarz, S., Gegov, A.: A New Computational Method for Solving Fully Fuzzy Nonlinear Systems. In: 10th International Conference Computational Collective Intelligence, ICCCI 2018, Bristol, UK, 5–7 Sept. 2018

    Google Scholar 

  42. Jafari, R., Razvarz, S., Gegov, A.: A novel technique to solve fully fuzzy nonlinear matrix equations. In: 13th International Conference on Applications of Fuzzy Systems and Soft Computing: ICAFS 2018. Springer (2018)

    Google Scholar 

  43. Jafari, R., Razvarz, S., Gegov, A.: Solving differential equations with z-numbers by utilizing fuzzy Sumudu transform. In: Intelligent Systems and Applications, vol 869, pp. 1125–1138. Springer International Publishing (2018)

    Google Scholar 

  44. Paul, S., Yu, W., Jafari, R.: A method for bidirectional active vibration control of structure using discrete-time sliding mode. IFAC-PapersOnLine 51(13), 361–365 (2018)

    Article  Google Scholar 

  45. Jafari, R., Razvarz, S., Gegov, A.: End-to-end memory networks: a survey. In: Advances in Intelligent Systems and Computing. Springer (2019)

    Google Scholar 

  46. Jafari, R., Razvarz, S., Gegov, A., Vatchova, B.: A survey on applications of neuro-fuzzy models. In: Proceedings of the 10th IEEE International Conference on Intelligent Systems, 2019. Institute of Electrical and Electronics Engineers (2019)

    Google Scholar 

  47. Jafari, R., Razvarz, S., Yu, W., Gegov, A., Goodwin, M., Adda, M.: Genetic algorithm modeling for photocatalytic elimination of impurity in wastewater. In: Proceedings of SAI Intelligent Systems Conference, pp 228–236. Springer, Cham (2019)

    Google Scholar 

  48. Jafari, R., Razvarz, S., Gegov, A.: A novel technique for solving fully fuzzy nonlinear systems based on neural networks. Vietnam J. Comput. Sci. (2020)

    Google Scholar 

  49. Jafari, R., Razvarz, S., Gegov, A., Vatchova, B.: Deep learning for pipeline damage detection: an overview of the concepts and a survey of the state-of-the-art. In: Proceedings of the 10th IEEE International Conference on Intelligent Systems. Institute of Electrical and Electronics Engineers (2020)

    Google Scholar 

  50. Jafari, R., Razvarz, S., Vargas-Jarillo, C., Gegov, A.: Blockage detection in pipeline based on the extended Kalman Filter observer. Electronics 9(1), 91 (2020)

    Article  Google Scholar 

  51. Paul, S., Yu, W., Jafari, R.: Stability Analysis and Bidirectional Vibration Control of Structure. In: Emerging Trends in Civil Engineering, pp. 275–287. Springer, Singapore (2020)

    Chapter  Google Scholar 

  52. Jafarian, A., Jafari, R.: A new computational method for solving fully fuzzy nonlinear matrix equations. Int. J. Fuzzy Comp. Modell. 2(4), 275–285 (2019)

    Article  Google Scholar 

  53. Jafari, R., Razvarz, S.: Solution of fuzzy differential equations using fuzzy Sumudu transforms. In: 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 3–5 July 2017, pp. 84–89 (2017). https://doi.org/10.1109/INISTA.2017.8001137

  54. Jafari, R., Yu, W., Li, X., Razvarz, S.: Numerical solution of fuzzy differential equations with Z-numbers using Bernstein neural networks. Int. J. Comput. Intell. Syst. 10(1), 1226–1237 (2017)

    Article  Google Scholar 

  55. Razvarz, S., Jafari, R.: ICA and ANN modeling for photocatalytic removal of pollution in wastewater. Math. Comput. Appl. 22(3), 38 (2017b)

    Google Scholar 

  56. Razvarz, S., Jafari, R., Yu, W., Golmankhaneh, A.K.: PSO and NN modeling for photocatalytic removal of pollution in wastewater. In: 2017 14th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 20–22 Oct. 2017, pp 1–6 (2017). https://doi.org/10.1109/ICEEE.2017.8108825

  57. Jafari, R., Razvarz, S., Gegov, A.: A new computational method for solving fully fuzzy nonlinear systems. In: International Conference on Computational Collective Intelligence, pp. 503–512. Springer (2018)

    Google Scholar 

  58. Jafari, R., Razvarz, S., Gegov, A.: Solving differential equations with Z-numbers by utilizing fuzzy sumudu transform. In: Proceedings of SAI Intelligent Systems Conference, pp. 1125–1138. Springer, Cham (2018)

    Google Scholar 

  59. Jafari, R., Razvarz, S., Gegov, A.: Fuzzy differential equations for modeling and control of fuzzy systems. In: International Conference on Theory and Applications of Fuzzy Systems and Soft Computing, pp. 732–740. Springer, Cham (2018)

    Google Scholar 

  60. Jafari, R., Razvarz, S., Gegov, A., Paul, S.: Modeling and control of uncertain nonlinear systems. In: 2018 International Conference on Intelligent Systems (IS), 25–27 Sept. 2018, pp 168–173 (2018). https://doi.org/10.1109/IS.2018.8710463

  61. Jafari, R., Razvarz, S., Gegov, A.: Paul S Fuzzy modeling for uncertain nonlinear systems using fuzzy equations and Z-numbers. In: UK Workshop on Computational Intelligence, pp. 96–107. Springer (2018)

    Google Scholar 

  62. Razvarz, S., Jafari, R., Gegov, A., Paul, S.: Neural network approach to solving fully fuzzy nonlinear systems. In: Fuzzy Modeling and Control: Methods, Applications and Research, pp. 46–68. Nova Science Publishers, Inc. (2018)

    Google Scholar 

  63. Razvarz, S., Jafari, R., Granmo, O.-C., Gegov, A.: Solution of dual fuzzy equations using a new iterative method. In: Asian Conference on Intelligent Information and Database Systems, pp. 245–255. Springer (2018)

    Google Scholar 

  64. Razvarz, S., Jafari, R., Yu, W.: Numerical solution of fuzzy differential equations with Z-numbers using fuzzy Sumudu transforms. Adv. Sci. Technol. Eng. Syst. J. (ASTESJ) 3, 66–75 (2018)

    Google Scholar 

  65. Jafari, R., Razvarz, S., Gegov, A.: Neural Network Approach to Solving Fuzzy Nonlinear Equations using Z-Numbers. IEEE Trans. Fuzzy Syst., 1 (2019).https://doi.org/10.1109/TFUZZ.2019.2940919

  66. Jafari, R., Razvarz, S., Gegov, A., Paul, S., Keshtkar, S.: Fuzzy Sumudu transform approach to solving fuzzy differential equations with Z-numbers. In: Advanced Fuzzy Logic Approaches in Engineering Science, pp. 18–48. IGI Global (2019)

    Google Scholar 

  67. Belsito, S., Lombardi, P., Andreussi, P., Banerjee, S.: Leak detection in liquefied gas pipelines by artificial neural networks. AIChE J. 44(12), 2675–2688 (1998)

    Article  Google Scholar 

  68. Bicharra, A.C., Ferraz, I.N., Bernardini, F.C.: Artificial neural networks ensemble used for pipeline leak detection systems. In: Proceeding of the Seventh International Pipeline Conference, Alberta, Canada, Sept. 29–Oct. 3 2008. Citeseer (2008)

    Google Scholar 

  69. Shibata, A., Konishi, M., Abe, Y., Hasegawa, R., Watanabe, M., Kamijo, H.: Neuro based classification of gas leakage sounds in pipeline. In: 2009 International Conference on Networking, Sensing and Control, pp. 298–302. IEEE (2009)

    Google Scholar 

  70. Zhao, J., Li, D., Qi, H., Sun, F., An, R.: The fault diagnosis method of pipeline leakage based on neural network. In: 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, pp. 322–325. IEEE (2010)

    Google Scholar 

  71. Avelino AM, de Paiva JA, da Silva RE, de Araujo GJ, de Azevedo FM, Quintaes FdO, Maitelli AL, Neto AD, Salazar AO Real time leak detection system applied to oil pipelines using sonic technology and neural networks. In: 2009 35th Annual Conference of IEEE Industrial Electronics, 2009. IEEE, pp 2109–2114

    Google Scholar 

  72. Murvay, P.S., Silea, I.: A survey on gas leak detection and localization techniques. J. Loss Prev. Process Ind. 25(6), 966–973 (2012)

    Article  Google Scholar 

  73. Edson A (1962) Gas pipeline blast kills 8, 4 others hurt. The Montreal Gazette

    Google Scholar 

  74. NEWSGO.: Sombre anniversary in Lasalle: 50 years since gas explosion. CTV Montreal (2015)

    Google Scholar 

  75. Eldon, H.: Pipeline Explosion Kills Two Men. Sundre, Canada, Ottawa Citizen (1965)

    Google Scholar 

  76. Gordon, D.M.: Pipeline Explosion In Mexico Kills 52. The Telegraph, November 3 (1978)

    Google Scholar 

  77. Press, T.A.: 26 Killed in Mexico pipeline fire. CBCNEWS WORLD (2012)

    Google Scholar 

  78. Mosco, A.: Careless workers blamed for explosion. Observer-Reporter, June 6 (1989)

    Google Scholar 

  79. Mexico Pipeline Explosion Kills 26 Near US Border. Fox News (2012)

    Google Scholar 

  80. Anya, L.: Officials: W.Va. explosion was along newly installed natural gas line. Pittsburgh Post-Gazette Archived (2019)

    Google Scholar 

  81. Chris, L.: Explosion on Marshall County gas line heard and seen for miles.

    Google Scholar 

  82. Anya, L.: Landslide Caused West Virginia Pipeline Explosion. TransCanada reports, Pittsburgh Post-Gazette Archived (2018)

    Google Scholar 

  83. Jade, W.: Pipeline Explodes In Oklahoma. Huffington Post (2013)

    Google Scholar 

  84. Paul, S.: Nat Gas Pipeline Explosion Reported In Oklahoma (2016).

    Google Scholar 

  85. Millage, K.: Timeline of Bellingham pipeline explosion. Bellingham Herald (2016)

    Google Scholar 

  86. Ayodele, D.: Military Launches Attack on Militants Base in Ogun Coastal Communities. Information Nigeria (2017)

    Google Scholar 

  87. Stevenson, M.: Mexico Blast a Blow to Pemex's Improving Safety (2012)

    Google Scholar 

  88. Kinder Morgan must defend fatal Mexican gas pipeline explosion court case (2016)

    Google Scholar 

  89. Langford, C.: Kinder Morgan on Hook for Blast That Killed 22. Courthouse News Service (2016)

    Google Scholar 

  90. Ellingwood, K.: 27 Die in Oil Pipeline Explosion in Mexico. The Los Angeles Times Retrieved December 22 (2010)

    Google Scholar 

  91. Mexican pipeline explosion all but wipes out tiny town UPI. Morning News (Wilmington, Delaware: 2 (1978)

    Google Scholar 

  92. Government of Canada, Transportation Safety Board of Canada

    Google Scholar 

  93. https://www.reuters.com/article/us-pemex-fire/fire-at-mexico-pemex-gas-facility-kills-26-idUSBRE88H1DA20120919 (2012)

    Google Scholar 

  94. No Alarm Sounded When The West Virginia Pipeline Exploded : The Two-Way. NPR 2012-12-13 Retrieved 2016-10-04

    Google Scholar 

  95. Va, W.: gas explosion burns homes, shuts I-77. usatoday

    Google Scholar 

  96. Clayton, M.: West Virginia Gas Pipeline Explosion-Just a Drop in the Disaster Bucket. The Christain Science Monitor (2012)

    Google Scholar 

  97. San Bruno Explosion: Photos Of The Fire's Aftermath Paint A Bigger Picture. Retrieved on 8 Nov. 2011

    Google Scholar 

  98. Pipeline Accident Report, Natural Gas-Fuelled Building Explosion and Resulting Fire. New York City, National Transportation Safety Board, NTSB/PAR-15/01 PB2015–104889

    Google Scholar 

  99. Sanchez, R.: New York Explosion Exposes Nation's Aging and Dangerous Gas Mains. CNN (2014)

    Google Scholar 

  100. Groeger, L.: Pipelines Explained: How Safe are America’s 2.5 Million Miles of Pipelines ProPublica (2012)

    Google Scholar 

  101. Watts, J.: China’s Worst-Ever Oil Spill Threatens Wildlife as Volunteers Assist in Clean-Up. The Guardian (2010)

    Google Scholar 

  102. Chen, C.: Huge Pipeline Explosion in Northeastern China Causes Oil Spill. EPOCH TIMES (2015)

    Google Scholar 

  103. Edukugho, E.: Oil Pipeline Vandalism: What We Lost. Vanguard (2013)

    Google Scholar 

  104. Usman, E.: How vandals ambush, kill five JTF operatives in Arepo. Vanguard (2016)

    Google Scholar 

  105. Canadian, P.: Canadian Natural Resources Pipeline Leaks Near Slave Lake. CBC News, The Canadian Press (2014)

    Google Scholar 

  106. Gemmell.: Alta Oil Pipeline Leaked 28,000 Barrels. The Canadian Press CBC News (2011)

    Google Scholar 

  107. Torres, N.: Murphy Oil Reports Alberta Condensate Leak Now 17,000. Petro Global News (2015)

    Google Scholar 

  108. Madrazo, C.: 12 Lose Lives in Vast Lake of Blazing Oil. The Sydney Morning Gerald, New York (1959)

    Google Scholar 

  109. Lannon, A.: Eight Settle Claims Over Kanawha County Gas Pipeline Explosion. News Work TV, TriStateupdate (2013)

    Google Scholar 

  110. Shea, P.: Nat Gas Pipeline Explosion Reported In Oklahoma. The ValueWalk 20 (2013)

    Google Scholar 

  111. Emmanuel, A.: Preventable Errors Led to Pipeline Spill, Inquire Finds. Michigan, The New York Times (2012)

    Google Scholar 

  112. Millage, K.: Timeline of Bellingham Pipeline Explosion. The Bellingham Herald (2009)

    Google Scholar 

  113. Foster, J.M.: Natural Gas Pipeline Explosion Levels Homes in Kentucky Town. CLIMATEPROGRESS (2014)

    Google Scholar 

  114. Bouchard, C., Harquail, M., Simpson, C., Tadros, W.A.: Natural Gas Pipeline Rupture,Trans Canada Pipeline Limited, . Transportation Safety Board of Canada, Report No;P96H0012 (1996)

    Google Scholar 

  115. China, D.: Chinese Oil Pipeline Explosion. Reuters, November 23 (2013)

    Google Scholar 

  116. Kadir, A.: Transmission Gas Pipeline Lecture Note, Gas Engineering and Management, School of Computing. University of Salford, Manchester, Science and Engineering (2005)

    Google Scholar 

  117. Beavers, A.J., Neil, G., Thompson, C.: Technologies External Corrosion of Oil and Natural Gas Pipelines, ASM Handbook, Vol.13C, Corrosion: Environments and Industries ASM International (2006)

    Google Scholar 

  118. C M Engineers’ Data Book. Institution of Mechanical Engineers, 4th edn.

    Google Scholar 

  119. Hatton, G.J., Pulici, M., Curti, G., Mansueto, M.: Deepwater Natural Gas Pipeline Hydrate Blockage caused by a Seawater Leak. Offshore Technology Conference (2002)

    Google Scholar 

  120. Report on The Crack Caused by Ice Formation in the Velero Mckee Refinery by The United States Chemical Safety and Hazard Investigation Board (CSB) (2008)

    Google Scholar 

  121. Fire From Ice. System failure case study 3 (08) (2009)

    Google Scholar 

  122. PRCI Pipeline Leak Detection Operation Improvements an Overview of Currently Available Leak Detection Technologies and US Regulations, Standards. In: 2011 Paper presented at the 6th Pipeline Technology Conference Hannover Germany

    Google Scholar 

  123. EQUIFAX.: Non Destructive Testing-Magnetic Particle Inspection. Werner Solken (2008–2016)

    Google Scholar 

  124. Beller, M.: Pipeline Inspection Utilizing Ultrasound Technology: On the Issue ofResolution. Pigging Products and Services Association (2007)

    Google Scholar 

  125. ESAB Knowledge Center, Radiographic and Ultrasonic Testing of Welds. Welding Inspection (2014)

    Google Scholar 

  126. Chis, T.: Pipeline Leak Detection Techniques. Anale Seria Informatica V (2007)

    Google Scholar 

  127. Davidson, R.: An introduction to Pipeline PIGGING. Halliburton Pipeline and Process Services, PIGing Products and Services Association (2002)

    Google Scholar 

  128. Geiger, G., Werner, T., Matko, D.: Leak detection and locating-a survey. In: PSIG annual meeting, 2003. Pipeline Simulation Interest Group (2003)

    Google Scholar 

  129. Kiss, K., Ranganath, S.: Online monitoring to assure structural integrity of nuclear reactor components. Int. J. Press. Vessels Pip. 34(1–5), 3–15 (1988)

    Article  Google Scholar 

  130. Ortiz-Villafuerte, J., Castillo-Duran, R., Alanso, G., Calleros-Micheland, G.: online monitoring system based on noise analysis. Nucl. Eng. Des. 236(220), 2394–2404 (2006)

    Article  Google Scholar 

  131. PHMSA Pipeline and Hazardous Materials Safety Administration—Guidance Manual for Operators of Small Natural Gas Systems Method of Detection A Leak, 4 (2002 )

    Google Scholar 

  132. Razvarz, S., Jafari, R., Vargas-Jarillo, C.: Modelling and analysis of flow rate and pressure head in pipelines. In: 2019 16th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 11–13 Sept. 2019, pp. 1–6 (2019)

    Google Scholar 

  133. Jafari, R., Razvarz, S., Vargas-Jarillo, C., Yu, W.: Control of flow rate in pipeline using PID controller. In: 2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC), 9–11 May 2019, pp 293–298 (2019)

    Google Scholar 

  134. Razvarz, S., Vargas-Jarillo, C., Jafari, R., Gegov, A.: Flow control of fluid in pipelines using PID controller. IEEE Access 7, 25673–25680 (2019)

    Article  Google Scholar 

  135. Razvarz, S., Vargas-Jarillo, C., Jafari, R.: Pipeline monitoring architecture based on observability and controllability analysis. In: 2019 IEEE International Conference on Mechatronics (ICM), 18–20 March 2019, pp 420–423 (2019)

    Google Scholar 

  136. Razvarz, S., Jafari, R., Vargas-Jarillo, C., Gegov, A., Forooshani, M.: Leakage detection in pipeline based on second order extended Kalman filter observer. IFAC-PapersOnLine 52(29), 116–121 (2019). https://doi.org/10.1016/j.ifacol.2019.12.631

    Article  Google Scholar 

  137. Papadopoulou, K.A., Shamount, M.N., Lennox, B., Mackay, D., Turner, J.T., Wang, X.: An evaluation of acoustic reflectometry for leakage and blockage detection. IMechE (2008). https://doi.org/10.1243/09544062JMES873

    Article  Google Scholar 

  138. Newell, R.D.: Mass Balance Leak Detect. Can it Work for You, ENTELEC (2006)

    Google Scholar 

  139. Geiger, G., Werner, T., Matko, P.: Leak detection and locating-a survey. In: 35th Annual PSIG Meeting, Bern, Switzerland (2003)

    Google Scholar 

  140. Corp, A.: New Leak Detection and Monitoring Technology Ensures of Pipelines. Press Release (2010)

    Google Scholar 

  141. Billmann, L., Isermann, R.: Leak detection methods for pipelines. IFAC Proc. 17(2), 1813–1818 (1984)

    Article  MATH  Google Scholar 

  142. Siebert, H., Klaiber, T.: Testing a method for leakage monitoring of a gasoline pipeline. Process Autom. 5, 91–96 (1980)

    Google Scholar 

  143. Verde, C.: Minimal order nonlinear observer for leak detection. J. Dyn. Sys. Meas. Control 126(3), 467–472 (2004)

    Article  Google Scholar 

  144. Verde, C.: Multi-leak detection and isolation in fluid pipelines. Control Eng. Pract. 9(6), 673–682 (2001)

    Article  Google Scholar 

  145. Verde, C., Sánchez-Parra, M.: Application of structural analysis to improve fault diagnosis in a gas turbine. Gas Turbines: 307 (2010)

    Google Scholar 

  146. Verde, C.: Leakage location in pipelines by minimal order nonlinear observer. In: Proceedings of the 2001 American Control Conference.(Cat. No. 01CH37148), pp. 1733–1738. IEEE (2001)

    Google Scholar 

  147. Carrera, R., Verde, C., Cayetano, R.: A SCADA expansion for leak detection in a pipeline. Sensors 2300(2320), 2340 (2015)

    Google Scholar 

  148. Angulo, M.T., Verde, C.: Second-order sliding mode algorithms for the reconstruction of leaks. In: 2013 Conference on Control and Fault-Tolerant Systems (SysTol), pp. 566–571. IEEE (2013)

    Google Scholar 

  149. Aamo, O.M., Smyshlyaev, A., Krstic, M., Foss, B.A.: Output feedback boundary control of a Ginzburg-Landau model of vortex shedding. IEEE Trans. Autom. Control 52(4), 742–748 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  150. Hauge, E,. Aamo, O.M., Godhavn, J.-M.: Model based pipeline monitoring with leak detection. In: Seventh IFAC Symposium on Nonlinear Control Systems, 2007. vol 1 (2007)

    Google Scholar 

  151. Jolly, W.D., Morrow, T.B., O’Brien, J.F., Spence, H.F., Svedeman, S.J.: New Methods for Rapid Leak Detection in Offshore Pipelines Reports Prepared for the Minerals Management Service US Department of Interior (1992)

    Google Scholar 

  152. Anastasopoulos, A., Kourousis, D., Bollas, K.: Acoustic emission leak detection of liquid filled buried pipeline. J. Acoust. Emiss. 27 (2009)

    Google Scholar 

  153. Fuchs, H.V., Riehle, R.: Ten years of experience with leak detection by acoustic signal analysis. Appl. Acoust. 33(1), 1–19 (1991). https://doi.org/10.1016/0003-682X(91)90062-J

    Article  Google Scholar 

  154. Randall, R.B.: Frequency Analysis. Bruel and Kjaer (1987)

    Google Scholar 

  155. Tashvaei, M., Beck, S.B., Staszewski, A.: Leakage detection in pipelines using cepstrum analysis. Inst. Phys. Publ. Meas Sci. Technol. 17, 367–372 (2006)

    Article  Google Scholar 

  156. Beck, S.B.M., Foong, J., Staszewski, A.: Wavelet and Ceptrum analyses of leaks in pipe networks. Progr. Indus. Math. ECMI (2004)

    Google Scholar 

  157. Santos, R.B., Almeida, W.S., Silva, FVd., Cruz, SLd., Fileti, A.M.F.: Spectral analysis for detection of leaks in pipes carrying compressed air. Chem. Eng. Trans. 32, 1363–1368 (2013). https://doi.org/10.3303/CET1332228

    Article  Google Scholar 

  158. Sarkar, DaS.: Review of pipeline hazard detection using vibration analysis method. Int. J. Mech. Prod. Eng. 3(1) (2015)

    Google Scholar 

  159. Lay-Ekuakille, A., Vergallo, P., Trotta, A.: Impedance method for urban water works: experimental frequency analysis for leakage detection. 15th IWADC Workshop (2010)

    Google Scholar 

  160. Lotfollahi-Yaghin, M.A., Hesari, M.A.: Using wavelet analysis in crack detection at the arch concrete dam under frequency analysis with FEM. World Appl. Sci. J. 3(4), 691–704 (2008)

    Google Scholar 

  161. Liew, K.M., Wang, Q.: Application of wavelet theory for crack identification in structure. J. Eng. Mech. 124, 152–157 (1998a)

    Google Scholar 

  162. Kim, H., Melhem, H.: Damage detection of structures by wavelet analysis Eng. Struct. 26, 347–362 (2004)

    Google Scholar 

  163. Zhong, S., Oyadiji, S.O.: Detection of cracks in S imply-supported beams by continuous wavelet transform of reconstructed modal data. Comput. Struct. 89, 127–148 (2011)

    Google Scholar 

  164. Gentile, A., Messina, A.: On the continuous wavelet transforms applied to discrete vibrational data for detecting open cracks in damaged beams. Int. J. Solids Struct. 40, 295–315 (2003)

    Article  MATH  Google Scholar 

  165. Rucka, M., Wilde, A.: Application of continuous wavelet transform in vibration based damage detection method for beams and plates. J. Sound Vib. 297, 536–550 (2006)

    Article  Google Scholar 

  166. Hong, J.C., Kim, Y.Y., Lee, H.C., Lee, Y.W.: Damage detection using the Lipschitz exponent estimated by the wavelet transform; applications to vibration modes of a beam. Int. J. Solids Struct. 39, 1803–1816 (2002)

    Article  MATH  Google Scholar 

  167. Kulkarni, P.G., Sahasrabudhe, A.D.: Application of wavelet transform for fault diagnosis of rolling element bearings. Int. J. Sci. Technol. Res. 2(4) (2013)

    Google Scholar 

  168. Zhong, S., Oyadiji, S.O.: Crack detection in simply supported beams using stationary wavelet transform of modal data. J. Vib. Acoust. 18, 169–190 (2011a)

    Google Scholar 

  169. Zhong, S., Oyadiji, S.O.: Crack detection in simply supported beams without baseline modal parameters by stationary wavelet transform of modal data. Mech. Syst. Sig. Process. 21, 1853–1884 (2007)

    Article  Google Scholar 

  170. Fan, X., Zuo, M.J., Wang, X.: Identification of weak ultrasonic signals in testing of metallic materials using wavelet transform. Inst. Phys. Publ. Smart Mater Struct. 15, 1531–1539 (2006)

    Article  Google Scholar 

  171. Ma, M., Liang, J., Sun, L., Wang, M.: SAR image segmentation based on SWT and improved AFSA. Third International Symposium on Intelligent Information Technology and Security Informatics (2010). https://doi.org/978-0-7695-4020-7/10

    Google Scholar 

  172. Prats-Montalbána, J.M., Cocchib, M., Ferrer, A.: N-way modelling for wavelet filter determination in multivariate image analysis. J. Chemo Metr. 29, 379–388 (2015)

    Article  Google Scholar 

  173. Seker, S., Karatoprak, E., Kayran, A.H., Senguler, T.: Stationary wavelet transform for fault detection in rotating machinery. Proc of SPIE 6763 (2007)

    Google Scholar 

  174. Jamaluddin, F.N., Ahmad, S.A., Bahari, S., Noor, M., Hassan, W.Z.W., Yaacob, A., Adam, Y.: Performance of DWT and SWT in muscle fatigue detection. In: 2015 IEEE Student Symposium in Biomedical Engineering and Science (ISSBES) (2015)

    Google Scholar 

  175. Backus, J.: The Acoustic Foundations of Music, 2nd edn. WW Norton and Company, New York (1977)

    Google Scholar 

  176. Mortazavi, S.H., Shahrtash, S.M.: Comparing de-noising performance of DWT, WPT, SWT and DT-CWT for partial discharge signal. J. Univers. Power Eng. Conf., 1–6 (2008)

    Google Scholar 

  177. Zhong, S., Oyadiji, S.O.: Crack detection in simply supported beams using stationary wavelet transform of modal data. ASME J. Vibr. Acoust. 18, 169–190 (2009)

    Google Scholar 

  178. Zhong, S., Oyadiji, S.O.: Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data. Comput. Struct. 89, 127–148 (2011)

    Google Scholar 

  179. Mortazavi, S.H., Shahrtash, S.M.: Comparing de-noising performance of DWT,WPT, SWT and DT-CWT for partial discharge signal. J. Univers. Power Eng. Conf., 1–6 (2008)

    Google Scholar 

  180. Chen, Y., Ma, H.: Signal de-noising in ultrasonic testing based on stationary wavelet transform. WRI Global Congr. Intell. Syst. (2009). https://doi.org/10.1109/GCIS.2009.266

    Article  Google Scholar 

  181. Zhong, S., Oyadiji, S.O.: Identification of cracks in beams with auxiliary mass spatial probing by stationary wavelet transform. ASME J. Vibr. Acoust. 130, 1–14 (2008)

    Google Scholar 

  182. Seker, S., Karatoprak, E., Kayran, A.H., Senguler, T.: Stationary wavelet transform for fault detection in rotating machinery. Proc. SPIE 6763, 67630A (2007)

    Article  Google Scholar 

  183. Lotfollahi-Yaghin, M.A., Hesari, M.A.: Using wavelet analysis in crack detection at the arch concrete dam under frequency analysis with FEM. World Appl. Sci. J. 3(4) (2008)

    Google Scholar 

  184. Liew, K.M., Wang, Q.: Application of wavelet theory for crack identification in structures. J. Eng. Mech. 124, 152–157 (1998b)

    Google Scholar 

  185. Kim, H., Melhem, H.: Damage detection of structures by wavelet analysis. Eng. Struct. 26, 347–362 (2004)

    Article  Google Scholar 

  186. Zhong, S.O., Yadiji, S.O.: Detection of cracks in simply-supported beams by continuous wavelet transform of reconstructed modal data. Comput. Struct. 89, 127–147 (2011)

    Google Scholar 

  187. Kulkarni, P.G., Sahasrabudhe, A.D.: Application of wavelet transform for fault diagnosis of rolling element bearings. Int. J. Sci. Technol. Res. 2(4) (2013)

    Google Scholar 

  188. Katunin, A.: Non-destructive damage assessment of composite structures based on wavelet analysis of modal curvatures: State-of-the-Art review and description of wavelet-based damage assessment benchmark, pp. 1–19. Hindawi Publishing Corporation Shock and Vibration (2015)

    Google Scholar 

  189. Zhong, S., Oyadiji, S.O.: Crack detection in simply supported beams using stationary wavelet transform of modal data. ASME J. Vibr. Acoust. 18, 169–190 (2011b)

    Google Scholar 

  190. Nagendra, H., Mukherjee, S., Kumar, V.: Application of wavelet techniques in ECG signal processing: an overview. Int. J. Eng. Sci. Technol. (IJEST) 3 10) (2011)

    Google Scholar 

  191. Kshirsagar, P., Salodkar, A., Bhaiswar, R.: Iris recognition using stationary wavelet transform and artificial neural network. Int. J. Eng. Innov. Technol. 1(3) (2012)

    Google Scholar 

  192. Zhong, S., Oyadiji, S.O.: Analytical predictions of natural frequencies of crack simply supported beams with a stationary roving mass. J. Sound Vib. 311, 328–352 (2008)

    Article  Google Scholar 

  193. Wang, Y., He, Z., Zi, Y.: A demodulation method based on improved local mean decomposition and its application in rub-impact fault diagnosis. Meas. Sci. Technol. 20, 1–10 (2009). https://doi.org/10.1088/0957-0233/20/2/02570

    Article  Google Scholar 

  194. Sakamoto, J.M.S., Baba, A., Tittmann, B.R., Mulry, J., Kropf, M., Pacheco, G.M.: Non-destructive inspection of a composite material sample using a laser ultrasonic system with a beam homogenizer. Rev. Progr. Quant. Nondestruct. Eval. 30(1335), 935–941 (2011). https://doi.org/10.1063/1.3592038

    Article  Google Scholar 

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Razvarz, S., Jafari, R., Gegov, A. (2021). A Review on Different Pipeline Defect Detection Techniques. In: Flow Modelling and Control in Pipeline Systems. Studies in Systems, Decision and Control, vol 321. Springer, Cham. https://doi.org/10.1007/978-3-030-59246-2_2

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