ABSTRACT
One of the best explored computational approaches to vibration-based damage detection is ANNs. The ANN technique has proven effective in damage detection due to its capability to model the nonlinear relationship between the vibration parameters and the damage location and severity (Wu, Ghaboussi et al. 1992, Barai and Pandey 1995, Masri, Nakamura et al. 1996, Zang and Imregun 2001, Lee, Lee et al. 2005, Pawar, Venkatesulu Reddy et al. 2006, Bakhary, Hao et al. 2007). The issues of uncertainty become more significant as civil engineering structures become more complex. There are two types of unavoidable uncertainties in the application of ANNs in damage detection: modeling error and measurement noise. Modeling error refers to the existence of uncertainties in the Finite Element model (FE model) due to the inaccuracy of physical parameters, non-ideal boundary conditions, finite element discretization and nonlinear structural properties that may result in the FE model not representing the exact behavior
an iterative process of simulation that is very time consuming.
