Early Damage Detection Based on Pattern Recognition and Data Fusion

AbstractStructural health monitoring (SHM) relies on data acquired from sensorial systems installed on site, and is nowadays being used more often not only for asset management, but also in critical structures when there is the need to detect damage in an early stage, before it impairs structural performance and safety. Early detection of damage in critical structures relies on the acquisition of continuous streams of information and on reliable techniques capable of analyzing it in real time, without generating false alerts. In this context, the combination of data fusion strategies, capable of converting large amounts of data into small pieces of information, with pattern recognition algorithms, which are able to analyze this information in real time, is addressed in the present paper with the objective of developing an original strategy capable of (1) removing the effects of regular actions imposed to structures without the need to measure them and of (2) compressing entire SHM data sets of arbitrary d...

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