  The lack of anomaly detection methods during mechanized tunnelling can cause
financial loss and deficits in drilling time. On-site excavation requires hard
obstacles to be recognized prior to drilling in order to avoid damaging the
tunnel boring machine and to adjust the propagation velocity. The efficiency of
the structural anomaly detection can be increased with intelligent optimization
techniques and machine learning. In this research, the anomaly in a simple
structure is detected by comparing the experimental measurements of the
structural vibrations with numerical simulations using parameter estimation
methods.
