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Damage identification for composite structures using a cross-correlation reverse-time migration technique

delete2015-09-11
delete70
PRE
AI
J
Jiaze He
F
Fuh‐Gwo Yuan *
DOI:10.1177/1475921715602546delete
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Abstract

Abstract

En 中文
This article presents a reverse-time migration technique to image damage by cross-correlating forward and backward propagating wavefields in composite structures using flexural wave signals. First, theory and procedures are presented for damage imaging for composite plates using a zero-lag cross-correlation imaging condition for reverse-time migration, briefly called cross-correlation-based reverse-time migration. The zero-lag cross-correlation was calculated between the forward wavefield and the backward wavefield. The forward wavefield is formed by the excitation from the actuator using a finite difference method, and the backward wavefield is generated by back-propagating the time-reversed scattered wavefield using the same finite difference method. Simulation studies were first examined to verify the capability of using the proposed zero-lag cross-correlation imaging condition to image single and multiple sites of damage. Two experiments were conducted where either the surface-mounted piezoelectric wafers or non-contact laser Doppler vibrometer was used for receiving the scattered wave signals along a linear array. The scattered wave signals were extrapolated in reverse-time to generate backward propagating wavefields. The experimental studies demonstrated that the cross-correlation-based reverse-time migration can accurately locate and image multiple sites of damage with improved resolution and higher efficiency in comparison with classical pre-stack reverse-time migration.
Keywords:
Damage identification
composite structures
reverse-time migration
zero-lag cross-correlation imaging condition
laser Doppler vibrometer
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Journal

S
Structural Health Monitoring-An International Journal
IF:
5.7
Papers:
2.3K
Citations:
1.1W

Organization

N
North Carolina State University
Scholars:
2.6W
Papers: 2.3W
Citations: 3.7W
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