- It was shown that the Mahalanobis distance comparison method was useful for the statistical m validation based on multivariate feature vectors. - Correlation of uncertain parameters in the numerical model greatly influences the success of Mahalanobis distance comparison. This issue should be considered both in the construction of a numerical model and in the response feature selection. The first and third issues should be advanced in the future works. They will become important considerations to realize more generalized structural dynamics model validation strategy and accurate uncertainty quantifications. References [1] Atamturktur, S., Hemez, F., Unal, C., Calibration under Uncertainty for Finite Element Models Masonry, LA-14414, Los Alamos, NM, Los Alamos National Laboratory, 2010. [2] Figueiredo, E., Park, G., Figueiras. J., Farrar, C., Worden, K., Structural Health Monitoring Algorithm Comparisons Using Standard Data Sets, LA-14393, Los Alamos, NM: Los Alamos National Laboratory, 2009. [3] Farrar, C., Worden, K., Todd, M., Park, G., Nichols, J., Adams, D., Bement, M., Farinholt, K., Nonlinear System Identification for Damage Detection, LA-14353, Los Alamos, NM: Los Alamos National Laboratory, 2007. [4] Hemez, F., Farrar, C., Lecture notes: Finite Element Model Validation, Updating, and Uncertainty Quantification, Los Alamos National Laboratory, 2009. [5] Robertson, A., Farrar, C., Sohn, H., Singularity Detection for Structural Health Monitoring using Holder exponent, Mechanical Systems and Signal Processing, Vol. 17, Issue 6, 1163-1184, 2003. [6] Worden, K., Manson, G., Fieller N.R.J., Damage Detection using Outlier Analysis, J. Sound and Vibration, 229 (3), 647-667, 2000. 163
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