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Knowledge Management: Intelligent In-pipe Inspection Robot Conceptual Design for Pipeline Infrastructure Management

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Intelligent Techniques in Engineering Management

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 87))

Abstract

Pipeline distribution and production are primary methods of transporting oil, natural gas, chemicals, and water. However, prolonged exposure to natural weather may cause corrosion, crack, and leakage to the pipelines. Therefore, periodical inspection is considered uttermost important. As most mechanised inspection techniques (e.g., non-destructive testing) are only deal with external inspect, they cannot accurately detect significant corrosion or other of defects in the internal. In addition, the inspection tasks can only be applied manually by highly trained operators. Given these circumstances, various concepts of pipeline inspection robots are developed in recent years to enhance the whole maintenance excellence. In this chapter, a multi-agent system (MAS) approach assisted intelligent conceptual design (ICD) platform is adopted for miniature in-pipe inspection robot design synthesizing. The demo case study shows that the proposed MAS-ICD can outperform human designers in many perspectives.

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Authors and Affiliations

  1. Computational Intelligence, Robotics, and Cybernetics for Leveraging E-Future (CIRCLE), Department of Computer Science, School of Mathematical and Computer Sciences, Faculty of Science and Agriculture, University of Limpopo, Private Bag X1106, Sovenga 0727, Limpopo, South Africa

    Bo Xing

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  1. Bo Xing
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Correspondence to Bo Xing .

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Editors and Affiliations

  1. Department of Industrial Engineering Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University Management Faculty, Istanbul, Turkey

    Sezi Çevik Onar

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Xing, B. (2015). Knowledge Management: Intelligent In-pipe Inspection Robot Conceptual Design for Pipeline Infrastructure Management. In: Kahraman, C., Çevik Onar, S. (eds) Intelligent Techniques in Engineering Management. Intelligent Systems Reference Library, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-319-17906-3_6

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  • DOI: https://doi.org/10.1007/978-3-319-17906-3_6

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