Non-classical nonlinear feature extraction from standard resonance vibration data for damage detection

J. N. Eiras, J. Monzó, J. Payá, T. Kundu, J. S. Popovics

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Dynamic non-classical nonlinear analyses show promise for improved damage diagnostics in materials that exhibit such structure at the mesoscale, such as concrete. In this study, nonlinear non-classical dynamic material behavior from standard vibration test data, using pristine and frost damaged cement mortar bar samples, is extracted and quantified. The procedure is robust and easy to apply. The results demonstrate that the extracted nonlinear non-classical parameters show expected sensitivity to internal damage and are more sensitive to changes owing to internal damage levels than standard linear vibration parameters.

Original languageEnglish (US)
Pages (from-to)EL82-EL87
JournalJournal of the Acoustical Society of America
Volume135
Issue number2
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics

Fingerprint

Dive into the research topics of 'Non-classical nonlinear feature extraction from standard resonance vibration data for damage detection'. Together they form a unique fingerprint.

Cite this