A spectrum-driven damage identification technique: Application and validation through the numerical simulation of the Z24 Bridge. (March 2016)

• Record Type: Journal Article
• Authors: Masciotta, Maria-Giovanna; Ramos, Luís F.; Lourenço, Paulo B.; Vasta, Marcello; De Roeck, Guido
• Is Part Of: Mechanical systems and signal processing. Volume 70/71(2016)
• Page Start: 578
• Page End: 600
• Publication Date: 2016-03
• Subjects: Damage identification -- Spectrum-driven method -- Damage localization index -- Power spectral densities -- Concrete bridges; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.08.027
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index. Highlights: A spectrum-driven approach for damage identification is proposed and validated through a numerical simulation. Changes in the system's stiffness caused by evolutionary damage scenarios lead to changes in the system's spectral response. The proposed method is based on the difference between damaged and undamaged spectral modes. The spectral damage localization index always detects the damage when existing and does not yield false negatives. Exciting the structure in the proximity of the damaged region may result in false positives.