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- W2898843564 abstract "The availability and reliability of tunnel infrastructure lies on the health of tunnel structure, therefore, scientific maintenance is needed to enhance the tunnel’s structure reliability and reduce the inspection and maintenance cost through optimized maintenance schedule. This paper aims to develop a data-driven framework for the operation and maintenance of tunnels, which consists of eight stages: maintenance data profile, tunnel failure mode and effect analysis (FMEA), data processing, feature engineering, anomaly detection, failure inspection, failure prediction and maintenance schedule. These Stages are interpreted into fifteen steps in a sub-system with data fusion techniques used for the whole process of tunnel components maintenance. The proposed framework for tunnel’s maintenance ensures the safety and reliability of tunnel’s operation, improves the efficiency of failure detection and reduces the maintenance cost as well." @default.
- W2898843564 created "2018-11-09" @default.
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- W2898843564 date "2018-11-05" @default.
- W2898843564 modified "2023-09-27" @default.
- W2898843564 title "A Data-Driven Framework for Tunnel Infrastructure Maintenance" @default.
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- W2898843564 doi "https://doi.org/10.1007/978-3-319-98776-7_54" @default.
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