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Inversion algorithm for Lamb-wave-based depth characterization of acoustic emission sources in plate-like structures.
Brennan Dubuc1, Arvin Ebrahimkhanlou1, Stylianos Livadiotis1
1Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, 301E E Dean Keeton St, Austin, TX 78712, USA.
Ultrasonics
|August 18, 2019
Summary
A new algorithm estimates acoustic emission (AE) source depth in plate-like structures by analyzing Lamb wave modes. This method aids in characterizing fatigue crack growth and shows potential for real-time structural health monitoring.
Area of Science:
- Structural Health Monitoring
- Materials Science
- Acoustics
Background:
- Early-stage fatigue crack growth in plate-like structures requires precise source localization.
- Acoustic emission (AE) signals contain information about source characteristics, including depth.
- Existing methods may lack the accuracy or speed for real-time applications.
Purpose of the Study:
- To develop and validate an inversion algorithm (AEDep) for estimating the depth of AE sources.
- To characterize fatigue crack growth in plate-like components using AE.
- To assess the algorithm's potential for real-time structural health monitoring.
Main Methods:
- Developed an inversion algorithm (AEDep) utilizing depth-dependent amplitude ratios of fundamental Lamb modes in AE signals.
- Employed a finite element model to simulate frequency-dependent Lamb wave propagation and establish source depth-amplitude ratio relationships.
- Validated the model using elastodynamic theory and derived a sensor tuning factor.
- Conducted experiments on aluminum plates and aircraft fuselage panels using controlled AE sources (Hsu-Nielsen pencil lead breaks).
Main Results:
- The AEDep algorithm accurately estimated AE source depths in a 6061-T6 aluminum plate.
- A slight reduction in accuracy was observed for the aircraft fuselage panel.
- The algorithm successfully distinguished between mid-plane and surface-originating sources in both specimens.
- The algorithm demonstrated fast computation, suitable for real-time monitoring.
Conclusions:
- The AEDep algorithm is effective for estimating AE source depth in plate-like structures.
- The method shows promise for characterizing fatigue crack growth and enabling real-time structural health monitoring.
- Further validation on diverse materials and structures is recommended.
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