A railway tunnel structural monitoring methodology proposal for predictive maintenance

Structural health monitoring (SHM) on railway tunnels is increasingly demanding inspection methodologies based on full-field image-based techniques. The relevance of adequate inspection methodologies to signal potential problems that need increased attention is at the forefront of any monitoring system for problems that can disturb tunnel's integrity. Detecting defects is decisive for an efficient inspection, investigating tunnel status, and rescheduling maintenance operations, when and where required. This paper introduces a methodology design, based on acquisition of tunnel's 3D geometry and monitoring it through time to signal the possible emergence of structural defects and return the exact position where monitoring equipment will have to be deployed to. A demonstrator is built, and the applicability and accuracy of the system is assessed through implementation of a model prototype, carried out on a scaled tunnel model. At a secondary stage inspection, imposed geometrical changes and defects of the tunnel are monitored and characterised by an optical nondestructive inspection technique based on the digital image correlation (DIC). It enables the appraisal of structural integrity on the tunnel lining through displacement and strain fields acquisition. The chief advantage of the deployed inspection system, amongst others, lies on its robust functionality in both geometrical and structural integrity inspection aspects, contributing to the establishment of a robust SHM methodology for railway tunnels over time. In conclusion, experimental results are presented for evaluating scaled tunnel condition and monitoring the tunnel profile, and further DIC data are presented inferring displacement field progress of an introduced structural defect.