Damage Identification in Steel Girder Based on Vibration Responses of Different Sinusoidal Excitations and Wavelet Packet Permutation Entropy

Abstract

Damage identification, both in terms of size and location, in bridges is important for timely maintenance and to avoid any catastrophic failure. An earlier experimental study showed that damage in a steel box girder orthotropic plate can be successfully detected using the measured vibration acceleration data. In this study, the wavelet packet decomposition (WPD) method is used to analyze the measured vibration acceleration responses and then the estimation of the permutation entropy (PE) on the re-constructed signals. A damage index is then defined based on the permutation entropy difference (PED) between the damaged and the healthy conditions to detect the location and size of the damage. The method is further validated through the finite element (FE) model of a steel box girder and the computed vibration acceleration responses when subjected to the sinusoidal excitations at different frequencies. In addition, the robustness of the methodology under different white noise interference conditions is also verified. The results show that the proposed methodology can effectively identify the location of human-made damage and accurately estimate the degree of damage under different frequencies of sinusoidal excitation. The method has shown a strong anti-noise property.