  Damage detection of mechanical structures such as bridges is an important
research problem in civil engineering. Using spatially distributed sensor time
series data collected from a recent experiment on a local bridge in upper state
New York, we study noninvasive damage detection using information-theoretical
methods. Several findings are in order. First, the time series data, which
represent accelerations measured at the sensors, more closely follow Laplace
distribution than normal distribution, allowing us to develop parameter
estimators for various information-theoretic measures such as entropy and
mutual information. Secondly, as damage is introduced by the removal of bolts
of the first diaphragm connection, the interaction between spatially nearby
sensors as measured by mutual information become weaker, suggesting that the
bridge is "loosened". Finally, using a proposed oMII procedure to prune away
indirect interactions, we found that the primary direction of interaction or
influence aligns with the traffic direction on the bridge even after damaging
the bridge.
