A bayesian framework for crack detection in structural components under dynamic excitation

M. Broggi, P. Beaurepaire, E. Patelli

Research output: Contribution to journalArticle

Abstract

Structures under dynamic excitation can undergo phenomena of crack growth and fracture. For safety reasons, it is of key importance to be able to detect and classify these cracks before the structural failure. Additionally, the cracks will also change the dynamic behaviour of the structures, impacting their performance. Here, a Bayesian model updating procedure has been introduced for the detection of crack location and length on a numerical model. A high-fidelity finite element model has been used to simulate experimental data, by inserting cracks of different lengths in different locations and obtaining reference frequency response function. Then, a low fidelity model has been used in the Bayesian framework to infer the crack location and length by comparing the dynamic responses. It is shown that the proposed technology can be successfully adopted as a structural health monitoring tool.

Original languageEnglish
Pages (from-to)127-132
Number of pages6
JournalChemical Engineering Transactions
Volume33
DOIs
Publication statusPublished - 20 Jul 2013

Keywords

  • Bayesian framework
  • crack detection
  • dynamic excitation

Fingerprint Dive into the research topics of 'A bayesian framework for crack detection in structural components under dynamic excitation'. Together they form a unique fingerprint.

  • Cite this