Narrow Results

Detection of incipient damage of structures at the earliest possible stage is desirable for successful implementation of any health monitoring system. In this paper, we focus on breathing crack problem and present a new reference-free algorithm for fatigue crack detection, localization, and characterization for beam-like structures. We use the spatial curvature of the Fourier power spectrum as a damage sensitive feature for fatigue crack identification. An exponential weighting function that takes into account nonlinear dynamic signatures, such as sub- and superharmonics, is proposed in the Fourier power spectrum in order to enrich the damage-sensitive features of the structure. Both numerical and experimental studies have been carried out to test and verify the proposed algorithm.

The identification of a breathing crack is a highly challenging inverse problem in structural health monitoring. A novel output-only diagnostic technique for breathing cracks is proposed in this paper based on the singular value decomposition (SVD). A new damage index based on the singular values of the harmonic time history response, related to the Fourier spectrum amplitude of the superharmonics, is presented for breathing crack localization. The robustness and effectiveness of the proposed SVD-based approach are verified through both numerical and experimental studies.