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Damage detection of mechanical structures such as bridges is an importantresearch problem in civil engineering. Using spatially distributed sensor timeseries data collected from a recent experiment on a local bridge in upper stateNew York, we study noninvasive damage detection using information-theoreticalmethods. Several findings are in order. First, the time series data, whichrepresent accelerations measured at the sensors, more closely follow Laplacedistribution than normal distribution, allowing us to develop parameterestimators for various information-theoretic measures such as entropy andmutual information. Secondly, as damage is introduced by the removal of boltsof the first diaphragm connection, the interaction between spatially nearbysensors as measured by mutual information become weaker, suggesting that thebridge is "loosened". Finally, using a proposed oMII procedure to prune awayindirect interactions, we found that the primary direction of interaction orinfluence aligns with the traffic direction on the bridge even after damagingthe bridge.

Information theoretical noninvasive damage detection in bridge structures