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A Fast Beamforming Method to Localize an Acoustic Emission Source under Unknown Wave Speed
Junfei Tai1, Tian He2, Qiang Pan3
1School of Transportation Science and Engineering, Beihang University, Beijing 100083, China. taijunfei@buaa.edu.cn.
This study introduces a fast beamforming method (FBBM) for accurately locating acoustic emission sources in thin-walled structures. The FBBM significantly speeds up damage source localization without needing prior knowledge of wave speed.
Area of Science:
- Structural Health Monitoring
- Acoustic Emission Testing
- Wave Propagation Analysis
Background:
- Traditional beamforming methods for acoustic emission source localization in large structures are accurate but time-consuming and sensitive to wave speed assumptions.
- Online monitoring of thin-walled structures requires efficient and robust damage localization techniques.
Purpose of the Study:
- To propose a fast and accurate method for localizing acoustic emission sources in thin-walled structures, even with unknown wave speeds.
- To adapt the Bartlett beamforming method (BBM) for broadband Lamb wave signal processing in thin-walled structures.
- To develop a computationally efficient algorithm for real-time damage source identification.
Main Methods:
- Introduction of the Bartlett beamforming method (BBM) for processing broadband Lamb wave signals.
- Development of a fast Bartlett beamforming method (FBBM) leveraging BBM characteristics for enhanced speed.
- Validation using pencil-lead break tests on thin-walled structures with an L-shape array.
Main Results:
- The proposed fast beamforming method (FBBM) accurately localizes acoustic emission damage sources.
- FBBM demonstrates significantly higher speed compared to traditional delay-and-sum beamforming.
- The method effectively handles unknown wave speeds in thin-walled structures.
Conclusions:
- The fast Bartlett beamforming method (FBBM) offers a rapid and accurate solution for acoustic emission source localization in thin-walled structures.
- FBBM overcomes the limitations of traditional methods regarding wave speed dependency and processing time.
- This technique is suitable for online monitoring applications requiring efficient damage detection.
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