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

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

Yujia Hu, Weigong Guo, Weidong Zhu and Yongfeng Xu
Mechanical systems and signal processing, Vol.131, pp.633-648
15/09/2019

Abstract

Bayesian operational modal analysis Damage detection Digital image correlation Membrane
•A novel noncontact local damage detection method is proposed for membranes.•Advantages of 3D-DIC and BOMA are integrated.•Modal parameters of a membrane can be identified under ambient excitation.•Use of a mode shape damage index can improve local damage detection. 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.

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