Intelligent Optimization and Machine Learning Algorithms for Structural Anomaly Detection using Seismic Signals

Possible unfavourable scenarios span from excess water inflow or a damaging of the Tunnel Boring Machine (TBM) to a total collapse of the tunnel [1]. To avoid potential risks, the imaging of voids, faults, fluid areas, erratic boulders or other changes in material is essential. Exploratory drillings only provide an image of the geological parameters in the near-field of the borehole and lack in showing the detailed geological structure. Thus, acoustic analysis is a better choice as it offers the opportunity to obtain a detailed image of the soil with the help of seismic waves. Propagating through the ground, seismic waves are reflected, refracted, scattered and converted; resulting in a detailed fingerprint of the actual structure. Most of the techniques used nowadays for the detection of anomalies rely on travel time measurements and migration techniques, considering only compressional waves.