Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7819
Title: Quantitative evaluation of orientation-specific damage using elastic waves and probability-based diagnostic imaging
Authors: Zhou, C
Su, Z 
Cheng, L 
Keywords: Damage identification
Lamb waves
Orientation-specific damage
Probability-based diagnostic imaging
Signal processing
Issue Date: 2011
Source: Mechanical systems and signal processing, 2011, v. 25, no. 6, p. 2135-2156 How to cite?
Journal: Mechanical Systems and Signal Processing 
Abstract: Different from the damage with relatively smooth boundaries or edges such as a through-thickness hole or delamination which scatters elastic waves omnidirectionally, orientation-specific damage of sizable length in a particular dimension (e.g., a crack or a notch) often exerts strong directivity to elastic wave propagation. As a consequence the damage-scattered waves may not be captured efficiently by sensors at certain locations, posing a challenging issue to elastic-wave-based damage identification. In this study, the influence of damage orientation on Lamb wave propagation was quantitatively scrutinised. Based on the established correlation between damage parameters (location, orientation, shape and size) and extracted signal features, a probability-based diagnostic imaging approach was developed, in conjunction with use of an active sensor network in conformity to a pulseecho configuration. Relying on enhancive signal features including both the temporal information and signal intensity, this imaging approach is capable of indicating the orientation of individual damage edges clearly and further shape/size of the damage. The effectiveness of the approach was demonstrated by predicting orientation-specific damage cases including a triangular through-thickness hole (through finite element simulation), a through-thickness crack and an L-shape crack (through experiment) in aluminium plates. With the assistance of a two-level synthetic image fusion scheme, all damage cases were visually and quantitatively highlighted in the probability images.
URI: http://hdl.handle.net/10397/7819
ISSN: 0888-3270
DOI: 10.1016/j.ymssp.2011.02.001
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