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

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

Research output: Contribution to journalArticle

17 Citations (Scopus)

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)
JournalJournal of the Acoustical Society of America
Volume135
Issue number2
DOIs
StatePublished - 2014

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pattern recognition
damage
vibration
linear vibration
vibration tests
frost
cements
sensitivity
Damage
Feature Extraction
Mortar
Diagnostics

ASJC Scopus subject areas

  • Acoustics and Ultrasonics
  • Arts and Humanities (miscellaneous)

Cite this

Non-classical nonlinear feature extraction from standard resonance vibration data for damage detection. / Eiras, J. N.; Monzó, J.; Payá, J.; Kundu, Tribikram; Popovics, J. S.

In: Journal of the Acoustical Society of America, Vol. 135, No. 2, 2014.

Research output: Contribution to journalArticle

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