ABSTRACT

The planning and the management of existing tunnels is already a central challenge for industrialized countries. Since an increasing amount of the tunnel industry employs mechanized excavation method, the effort put into the management and maintenance of the aforementioned underground structures will significantly increase in the next years. Tunnel inspection and diagnostic are a crucial task in providing reliable predictive tunnel maintenance at cost with time consuming and error-prone process if based on human operations only. Therefore, the diagnostic process of tunnel inspection and the relevant analytical procedures are suitable to automation. ETS and its partners have carried out the diagnostic and the maintenance of existing mechanized tunnels through an innovative multi-dimensional survey system (ARCHITA), and a new approach for the Management and Identification of the Risk for Existing Tunnels (MIRET). The MIRET approach and a deep learning test are demonstrated by its application to a case study.