4.7 Article

Local damage detection of membranes based on Bayesian operational modal analysis and three-dimensional digital image correlation

期刊

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 131, 期 -, 页码 633-648

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2019.04.051

关键词

Damage detection; Bayesian operational modal analysis; Digital image correlation; Membrane

资金

  1. Shanghai Natural Science Foundation [17ZR1419800]
  2. Shanghai Science and Technology Innovation Fund [17060502600]
  3. National Science Foundation [1335024, 1763024, 1762917]
  4. Directorate For Engineering
  5. Div Of Civil, Mechanical, & Manufact Inn [1763024] Funding Source: National Science Foundation
  6. Div Of Civil, Mechanical, & Manufact Inn
  7. Directorate For Engineering [1762917, 1335024] Funding Source: National Science Foundation

向作者/读者索取更多资源

It is difficult to detect local damage of a structure based on modal analysis. This paper presents a novel local damage detection method of membranes under ambient excitation, which combines Bayesian operational modal analysis (BOMA) and three-dimensional digital image correlation (3D-DIC). It is a noncontact and full-field dynamic method with no sensors attached on a test membrane. Advantages of BOMA and 3D-DIC methods are integrated in this work. Anomalies caused by local damage in mode shapes and curvature mode shapes can be explicitly observed. Moreover, a mode shape damage index (MSDI) is used to improve local damage detection, and structural damage can be identified in neighborhoods with high values of MSDIs. The methodology is applied, as a demonstration, to detect damage introduced by razor cuts in circular and rectangular membranes with different boundary conditions. (C) 2019 Published by Elsevier Ltd.

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