Narrow Results

The majority of the existing damage diagnostic techniques are based on linear models. Changes in the state of the dynamics of these models, before and after damage in the structure based on the vibration measurements, are popularly used as damage indicators. However, the system may initially behave linearly and subsequently exhibit nonlinearity due to the incipience of damage. Breathing cracks that exhibit bilinear behavior are one such example of the damage induced due to nonlinearity. Further many real world structures even in their undamaged state are nonlinear. Hence, in this paper, we present a nonlinear damage detection technique based on the adaptive Volterra filter using the nonlinear time history response. Three damage indices based on the adaptive Volterra filter are proposed and their sensitiveness to damage and noise is assessed through two numerically simulated examples. Numerical investigations demonstrate the effectiveness of the adaptive Volterra filter model to detect damage in nonlinear structures even with measurement noise.

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.

This study proposes a time-domain spectral finite element (SFE) method for simulating the second harmonic generation (SHG) of nonlinear guided wave due to material, geometric and contact nonlinearities in beams. The time-domain SFE method is developed based on the Mindlin–Hermann rod and Timoshenko beam theory. The material and geometric nonlinearities are modeled by adapting the constitutive relation between stress and strain using a second-order approximation. The contact nonlinearity induced by breathing crack is simulated by bilinear crack mechanism. The material and geometric nonlinearities of the SFE model are validated analytically and the contact nonlinearity is verified numerically using three-dimensional (3D) finite element (FE) simulation. There is good agreement between the analytical, numerical and SFE results, demonstrating the accuracy of the proposed method. Numerical case studies are conducted to investigate the influence of number of cycles and amplitude of the excitation signal on the SHG and its performance in damage detection. The results show that the amplitude of the SHG increases with the numbers of cycles and amplitude of the excitation signal. The amplitudes of the SHG due to material and geometric nonlinearities are also compared with the contact nonlinearity when a breathing crack exists in the beam. It shows that the material and geometric nonlinearities have much less contribution to the SHG than the contact nonlinearity. In addition, the SHG can accurately determine the crack location without using the reference data. Overall, the findings of this study help further advance the use of SHG for damage detection.

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.

The identification of a breathing crack is a highly challenging inverse problem in structural health monitoring. A novel output-only damage diagnostic technique based on Principal Component Analysis (PCA) is proposed for breathing crack identification in structures excited by harmonic excitation. The proposed approach basically utilizes the residues obtained from PCA of the forced acceleration-time history responses of the structure for breathing crack identification. In this approach, the traditional single-tone, bitone and as well as multi-tone harmonic excitations are considered as input to the structure while exploring the residues of the responses for breathing crack identification. A new Damage Localization Index (DLI) based on the Fourier spectrum amplitudes of the nonlinear sensitive features (i.e. buried in residues), measured at varied locations spatially across the structure is proposed for breathing crack localization. The robustness and effectiveness of the proposed PCA-based breathing crack localization approach is verified through both numerical and experimental studies.