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The application of black-box modeling in long-term tunnel deformation monitoring

Tunnel closures related to maintenance and reconstruction works can lead to large economical costs and should therefore be avoided. This paper explores the use of novelty detection algorithms for long-term tunnel monitoring. The aim is to detect tunnel damage in an early stage, as such providing a tool to support the asset management. The proposed strategy is applied to the monitoring of the Waasland tunnel in Antwerp, where the deformations and temperatures have been monitored over a period of 14 months. The case demonstrates that novelty detection by means of principal component analysis enables the identification of minor changes in the tunnel response, and can therefore be embedded in an early detection warning system.