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http://dx.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  

Hu, Yujia (School of Mechanical Engineering, University of Shanghai for Science and Technology)
Sun, Xi (School of Mechanical Engineering, University of Shanghai for Science and Technology)
Zhu, Weidong (2Department of Mechanical Engineering, University of Maryland)
Li, Haolin (School of Mechanical Engineering, University of Shanghai for Science and Technology)
Publication Information
Smart Structures and Systems / v.24, no.5, 2019 , pp. 597-606 More about this Journal
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.
Keywords
three-dimensional digital image correlation; Bayesian operational modal analysis; local damage detection;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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