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Smart Structures and Systems
  Volume 24, Number 5, November 2019 , pages 597-606
DOI: https://doi.org/10.12989/sss.2019.24.5.597
 


Local damage detection of a fan blade under ambient excitation by three-dimensional digital image correlation
Yujia Hu, Xi Sun, Weidong Zhu and Haolin Li

 
Abstract
    Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.
 
Key Words
    three-dimensional digital image correlation; Bayesian operational modal analysis; local damage detection
 
Address
Yujia Hu, Xi Sun and Haolin Li: School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Weidong Zhu: Department of Mechanical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
 

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