• Plataforma de vídeos del IIT
  • Twitter
  • LinkedIn
  • Asociación de Ingenieros del ICAI
  • Intranet
  • Spanish
Go top
Paper information

Civil structure condition assessment by a two-stage FE model update based on neural network enhanced power mode shapes and an adaptive roaming damage method

R. Perera, S. Sandercock, A. Carnicero

Engineering Structures Vol. 207, nº. 110234, pp. 1 - 15

Summary:
Vibration-based damage identification of large and complex structures requires a huge computational effort to solve an ill-posed inverse problem with a large number of unknowns. Moreover, due to the limited number of measurement sensors, the capability to detect damage is quite limited. To mitigate these disadvantages, a two-stage model updating method based on the proposed novel localised damage function approach called roaming damage method (RDM) is proposed. The roaming damage method has the ability to identify a wide range of damage types, from large areas of low damage to individual beams which have been severely damaged. The approach can be applied to complex and refined 3D finite element models in only two steps. To enhance identification, the optimization procedure is formulated in a multi-objective context dependent on a spectrum-driven feature that is based on the Power Mode Shapes (PMS) from measured responses. Unlike conventional mode shapes, PMSs contain information from the entire frequency range. The well-known case study of the I-40 bridge in New Mexico is chosen to apply and further investigate this technique with the aim of testing its reliability. The simulated dynamic data obtained from random vibrations are employed to evaluate the performance of the method. Two additional features to improve the proposal, the ANN enhanced PMS RMD and RDM with adaptive radius, have also been explored.


Keywords: Multistage damage identification; Roaming damage method; Power mode shapes; Neural networks; Large structures; Adaptive method


JCR Impact Factor and WoS quartile: 3.548 - Q1 (2019)

DOI reference: DOI icon 10.1016/j.engstruct.2020.110234

Published on paper: March 2020.

Published on-line: January 2020.



Citation:
R. Perera, S. Sandercock, A. Carnicero. Civil structure condition assessment by a two-stage FE model update based on neural network enhanced power mode shapes and an adaptive roaming damage method. Engineering Structures. Vol. 207, nº. 110234, pp. 1 - 15 March 2020. [Online: January 2020]


    Research topics:
  • Numerical modelling
  • Structural analysis

pdf Previsualizar
pdf Solicitar el artículo completo a los autores



We use our own and third-party cookies to improve the functionality of our website and the quality of our service, by analyzing your browsing habits.
For more information about cookies and how to refuse them, please visit our Cookies Policy.



EU Cookie Directive by www.iit.comillas.edu