Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16048
Title: Fatigue damage localization using time-domain features extracted from nonlinear lamb waves
Authors: Hong, M
Su, Z 
Lu, Y
Cheng, L 
Keywords: Fatigue damage
Lamb waves
Nonlinear ultrasonics
Piezoelectric sensor network
Structural health monitoring
Time of flight
Issue Date: 2014
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2014, v. 9064, 906405 (CD-ROM) How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
Abstract: Nonlinear guided waves are sensitive to small-scale fatigue damage that may hardly be identified by traditional techniques. A characterization method for fatigue damage is established based on nonlinear Lamb waves in conjunction with the use of a piezoelectric sensor network. Theories on nonlinear Lamb waves for damage detection are first introduced briefly. Then, the ineffectiveness of using pure frequency-domain information of nonlinear wave signals for locating damage is discussed. With a revisit to traditional gross-damage localization techniques based on the time of flight, the idea of using temporal signal features of nonlinear Lamb waves to locate fatigue damage is introduced. This process involves a time-frequency analysis that enables the damage-induced nonlinear signal features, which are either undiscernible in the original time history or uninformative in the frequency spectrum, to be revealed. Subsequently, a finite element modeling technique is employed, accounting for various sources of nonlinearities in a fatigued medium. A piezoelectric sensor network is configured to actively generate and acquire probing Lamb waves that involve damageinduced nonlinear features. A probability-based diagnostic imaging algorithm is further proposed, presenting results in diagnostic images intuitively. The approach is experimentally verified on a fatigue-damaged aluminum plate, showing reasonably good accuracy. Compared to existing nonlinear ultrasonics-based inspection techniques, this approach uses a permanently attached sensor network that well accommodates automated online health monitoring; more significantly, it utilizes time-domain information of higher-order harmonics from time-frequency analysis, and demonstrates a great potential for quantitative characterization of small-scale damage with improved localization accuracy.
Description: Health Monitoring of Structural and Biological Systems 2014, San Diego, CA, 10-13 March 2014
URI: http://hdl.handle.net/10397/16048
ISBN: 9780819499905
ISSN: 0277-786X (print)
1996-756X (online)
DOI: 10.1117/12.2044031
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