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Optimal pipe inspection paths considering inspection tool limitations

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  • Chen, Thomas Ying-Jeh
  • Guikema, Seth David
  • Daly, Craig Michael

Abstract

The inspection of deteriorating water distribution pipes is an important process for utilities. It helps them gain a better understanding of the condition of their buried conveyance systems and aids better decision making for risk-based asset management. In-pipe continuous inspection tools provide high resolution and accurate data, but they have seen relatively limited use due to cost and operational constraints. To facilitate-cost efficient deployment of these technologies and maximal information gain, a process that finds high risk pipes to inspect while accounting for the limitations of the tools at hand is needed. This paper shows how to incorporate these considerations within an optimization formulation, and examines the use of Evolutionary Programming, Simulated Annealing, and Greedy Search heuristics to identify inspection paths. Case studies performed on both synthetic and real world networks demonstrate that Evolutionary Programs are the most effective. While only three factors are used to characterize tool limitations, the method presented in this paper can be extended to include technology-specific complexities in real world applications.

Suggested Citation

  • Chen, Thomas Ying-Jeh & Guikema, Seth David & Daly, Craig Michael, 2019. "Optimal pipe inspection paths considering inspection tool limitations," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 156-166.
    • Handle: RePEc:eee:reensy:v:181:y:2019:i:c:p:156-166
    DOI: 10.1016/j.ress.2018.09.019
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    References listed on IDEAS

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    1. Francis, Royce A. & Guikema, Seth D. & Henneman, Lucas, 2014. "Bayesian Belief Networks for predicting drinking water distribution system pipe breaks," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 1-11.
    2. Laporte, Gilbert, 1992. "The traveling salesman problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(2), pages 231-247, June.
    3. Mancuso, A. & Compare, M. & Salo, A. & Zio, E. & Laakso, T., 2016. "Risk-based optimization of pipe inspections in large underground networks with imprecise information," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 228-238.
    4. Aven, Terje, 2010. "On how to define, understand and describe risk," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 623-631.
    5. Yamijala, Shridhar & Guikema, Seth D. & Brumbelow, Kelly, 2009. "Statistical models for the analysis of water distribution system pipe break data," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 282-293.
    6. Emily M. Zechman, 2011. "Agent‐Based Modeling to Simulate Contamination Events and Evaluate Threat Management Strategies in Water Distribution Systems," Risk Analysis, John Wiley & Sons, vol. 31(5), pages 758-772, May.
    7. E. Downey Brill, Jr. & Shoou-Yuh Chang & Lewis D. Hopkins, 1982. "Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning," Management Science, INFORMS, vol. 28(3), pages 221-235, March.
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    Cited by:

    1. Ruiz Muñoz, G.A. & Sørensen, J.D., 2020. "Probabilistic inspection planning of offshore welds subject to the transition from protected to corrosive environment," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    2. Chen, Thomas Ying-Jeh & Riley, Connor Thomas & Van Hentenryck, Pascal & Guikema, Seth David, 2020. "Optimizing inspection routes in pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    3. Jensen, H.A. & Jerez, D.J., 2019. "A Bayesian model updating approach for detection-related problems in water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 100-112.
    4. Chen, Thomas Ying-Jeh & Guikema, Seth David, 2020. "Prediction of water main failures with the spatial clustering of breaks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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