Signal processing based damage detection in structures subjected to random excitations

Damage detection methodologies based on the direct examination of the nonlinear-nonstationary characteristics of the structure dynamic response may play an important role in online structural health monitoring applications. Different signal processing based damage detection methodologies have been proposed based on the uncovering of spikes in the high frequency component of the structural response obtained via Discrete Wavelet transforms, Hilbert-Huang transforms or high pass filtering. The performance of these approaches in systems subjected to different types of excitation is evaluated in this paper. It is found that in the case of random excitations, like earthquake accelerations, the effectiveness of such methodologies is limited. An alternative damage detection approach using the Continuous Wavelet Transform (CWT) is also evaluated to overcome this limitation. Using the CWT has the advantage that the central frequencies at which it operates can be defined by the user while the frequency bands of the detail functions obtained via DWT are predetermined by the sampling period of the signal.