Abstract

It is common to apply damage-sensitive features from vibration responses of a structure to assess structural damage. Few damage identification algorithms have focused on the material variation and measurement noise. For engineering practices, the material variation could be caused by many reasons and there always exists a certain level noise in measurement; those facts may affect the features that are used for structure monitoring and also lead to inaccurate assessment. In this research the authors have proposed a model to assess the statistical structural damage of a beam structure. The modal curvature-base feature was used to identify crack locations. The statistical damage databases were built by applying the Latin hypercube sampling method in Monte Carlo simulation. By mapping features of noised modal frequency to the statistical damage database, the damage probabilities among various crack depths were estimated; the statistical significance of damage level was examined by the t -test. Simulated beams and their experimental modal analysis data demonstrated the assessment procedures. The authors concluded that the proposed algorithm was robust and able to identify the damage of a free–free beam with uniform mass density and stiffness variations incorporated with noise in measured frequency.

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