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A method for detecting damage-induced nonlinearity in structures using weighting function augmented curvature approach

Structural damages can result in nonlinear dynamical signatures that can significantly enhance their detection. In this article, we present a new method for identifying damage-induced nonlinearity using vibration response measurements. Among the various types of damages that induce nonlinearity, we focus on the breathing crack. We use the spatial curvature of Fourier power spectrum augmented with rectangular weighting function as a damage-sensitive feature for breathing crack identification. The proposed rectangular weighting function significantly enhances the resolution of superharmonics and intermodulation exhibited by the frequency domain response of the structure with breathing crack for breathing crack identification and characterization. The proposed algorithm is simple, does not involve any complex post-processing and also does not require any numerical model. Both numerical and experimental studies have been carried out to test and verify the proposed algorithm.