Tailored excitations for structural health monitoring via evolutionary programming

Dynamic interrogation of structures for the purposes of damage identification is an active area of research within the field of structural health monitoring with recent work focusing on the use of chaotic excitations and state-space analyses for improved damage detection. Inherent in this overall approach is the specific interaction between the chaotic input and the structure's eigenstate. The sensitivity to damage is theoretically enhanced by special tailoring of the input in terms of stability interaction with the structure. This work outlines the use of an evolutionary program to search the parameter space of a chaotic excitation for those parameters that are best suited to appropriately couple the excitation with the structure for enhanced damage detection. State-space damage identification metrics are used to detect damage in a computational model driven by excitations produced via the evolutionary program with non-optimized excitations used as comparison cases.

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