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    An ontological approach for pathology assessment and diagnosis of tunnels

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    Publication date
    2020-04
    Author
    Dimitrova, V.
    Mehmood, M.O.
    Thakker, Dhaval
    Sage-Vallier, B.
    Valdes, J.
    Cohn, A.G.
    Keyword
    Tunnel diagnosis
    Ontology
    Intelligent decision support systems
    Linear transport structures
    Rights
    © 2019 Published by Elsevier Ltd. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Tunnel maintenance requires complex decision making, which involves pathology diagnosis and risk assessment, to ensure full safety while optimising maintenance and repair costs. A Decision Support System (DSS) can play a key role in this process by supporting the decision makers in identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key aspect is to identify which spatial stretches within a tunnel contain pathologies of similar kinds within neighbouring tunnel segments. This paper presents PADTUN, a novel intelligent decision support system that assists with pathology diagnosis and assessment of tunnels with respect to their disorders and diagnosis influencing factors. It utilises semantic web technologies for knowledge capture, representation, and reasoning. The core of PADTUN is a family of ontologies which represent the main concepts and relations associated with pathology assessment, and capture the decision process concerning tunnel maintenance. Tunnel inspection data is linked to these ontologies to take advantage of inference capabilities offered by semantic technologies. In addition, an intelligent mechanism is presented which exploits abstraction and inference capabilities. Thus PADTUN provides the world’s first semantically based intelligent DSS for tunnel maintenance. PADTUN was developed by an interdisciplinary team of tunnel experts and knowledge engineers in real-world settings offered by the NeTTUN EU Project. An evaluation of the PADTUN system is performed using real-world tunnel data and diagnosis tasks. We show how the use of semantic technologies allows addressing the complex issues of tunnel pathology inferencing, aiding in, and matching transportation experts’ expectations of decision support. The methodology is applicable to any linear transport structures, offering intelligent ways to aid with complex decision processes related to diagnosis and maintenance.
    URI
    http://hdl.handle.net/10454/17643
    Version
    Accepted manuscript
    Citation
    Dimitrova V, Mehmood MO, Thakker D et al (2020) An ontological approach for pathology assessment and diagnosis of tunnels. Engineering Applications of Artificial Intelligence. 90: 103450.
    Link to publisher’s version
    https://doi.org/10.1016/j.engappai.2019.103450
    Type
    Article
    Collections
    Engineering and Informatics Publications

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