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| Reference | Author(s) | Damage detection method |
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| Reference document—No data | Johnson et al. [7, 8] | Detailed Description of Phase I—Simulated |
| Dyke et al. [9] | Detailed Description of Phase II—Experimental |
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| Phase I: Simulated data | Dyke et al. [10] | Loss of stiffness of members byoptimizing modal parameters |
| Hera et al. [11] | Spikes in Level 1 details of wavelet decomposed signals |
| Yang et al. [12] | Spectral analysis to identify stiffness parameters |
| Hera and Hou [13] | Spikes in Level 1 details of wavelet decomposed signals |
| Sun and Chang [14] | Covariance of response using wavelet packets |
| Lam et al. [15] | Loss of stiffness using modal update and identification |
| Yuen et al. [16] | Loss of stiffness of members using modal parameter extraction and Bayesian modal updating |
| Lus et al. and Caicedo et al. [17, 18] | State space model, eigensystem realization algorithm and optimization using modal parameters |
| Bernal and Gunes [19] | Extraction of a matrix proportional to structure flexibility |
| Lin et al. [20] | Time-frequency features obtained using Hilbert-Huang transform of the intrinsic mode functions |
| Chase et al. [21] | Recursive least square to identify changes in stiffness matrix |
| Wu and Li [22] | Eingen-sensitive FE for damage detection in ambient vibration |
| Yang and Huang [23] | A recursive nonlinear estimation method is used |
| Mizuno and Fujino [24] | Haar wavelet decomposition, quantization, and dissimilarity |
| Zhou et al. [25] | Residual values from subspace-modal identification |
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| Phase II: Simulated data | Hou and Hera [26] | Spikes in Level 1 details of wavelet decomposed signals using Daubechies and Meyer wavelets |
| Barroso and Rodriguez [27] | Comparison of healthy to damage curvature in the mode shapes |
| Casciati [28] | Discrepancy between healthy and damaged states using sum of squared errors |
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| Phase II: Simulated and experimental data | Hera and Hou [29] | Modal parameters determined using continuous wavelet transform |
| Dincal and Raich [30] | Minimization of error term between FRF of experimental & simulated data |
| Nair et al. [31] | Structural stiffness change based on poles; pattern classification with autoregressive coefficients |
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| Phase II: experimental data only | Ching and Beck [32, 33] | Expectation-Maximization algorithm used to find most probable stiffness parameters—Config. 2–9 |
| Giraldo et al. [34] | Loss of stiffness of members—Config 2–6 |
| Lynch [35] | Pole location using system identification, Config. 1–5 |
| Liu et al. [36] | Time-frequency obtained using Hilbert-Huang transform of intrinsic modes—Config. 7 & 8 |
| McCuskey et al. [37] and McCuskey [38] | Neural-wavelet module—All Configurations |
| Carden and Brownjohn [39] | Autoregressive moving average (ARMA) to build damage classifiers for different damage configurations |
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