  The paper proposes a method of damage detection in elastic materials, which
is based on analyzing the time-dependent (dynamic) response of the material
excited by an acoustic signal. A case study is presented consisting of
experimental measurements and their mathematical analysis. The decisive
parameters (wave speed and damping coefficient) of a mathematical model of the
acoustic wave are calibrated by comparing the measurement data with the
numerically evaluated exact solution predicted by the mathematical model. The
calibration is done both deterministically by minimizing the square error over
time and stochastically by a Bayesian approach, implemented through the
Metropolis-Hastings algorithm. The resulting posterior distribution of the
parameters can be used to construct a Bayesian test for damage.
