Monitoring tunneling induced ground displacements using distributed fiber-optic sensing

• Optical Brillouin and Rayleigh scattering are utilized for tunneling monitoring.
• Parameters of ground displacement models are estimated using fiber optic measurements.
• Two field investigations are presented of large and small diameter tunnels.
• The trough length can be estimated by investigation of peak strain location shift.

Determination and monitoring of tunneling induced ground displacement is an important component in tunneling design and construction. In recent years several technologies for distributed strain measurement along fiber optics have been developed, namely the Brillouin Optical Time Domain Reflectometry (or Analysis) – BOTDR/A and the Rayleigh backscatter wavelength interferometry (OBR). This paper presents how these technologies could be used to monitor and define ground displacement models through an appropriate 2D and 3D optimization and signal analysis of information derived from a horizontally laid fiber above the tunnel. The suggested approach is evaluated in two field investigations, one involving excavation of a 3 m diameter tunnel by TBM at depth of 18 m, and the other installation of a 1 m diameter water main by pipe-jacking at depth of 6 m. Comparison between the results obtained by the different technologies shows that they are equally suitable for the suggest approach. The suggests approach allows reliable determination of the parameters involved in empirical ground displacement models, and allows field validation that the tunneling process lies within the design bounds. An interesting observation, supported by the analytical models, is that non-perpendicular alignment of the fiber, relatively to the tunnel line, results in a shift in the peak strain location as the tunnel advances. It was demonstrated that the rate of change in peak strain location, with tunnel advancement, can be used to obtain the settlement trough length parameter, without the need for complete evaluation of all other model parameters.