We present an approach for detecting damage-induced nonlinearities in structures. The method first involves the creation of surrogate data sets conforming to an appropriate null hypothesis (no damage). The second step is to then compare some nonlinear “feature” extracted from the original data to those extracted from the surrogates. Statistically significant differences suggest evidence in favor of the alternative hypothesis, damage. Using this approach we show how loose connections can be detected using ambient “wave” forcing, conforming to the Pierson-Moskowitz distribution, as the source of excitation. We also demonstrate the ability of this technique to operate without a recorded baseline data set and in the presence of widely varying temperatures. The structure in this case is a thick, composite beam bolted to a steel frame. Data are collected using an optical strain sensing system. For this experiment we are able to reliably detect the presence of a loosened bolt.

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