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Published on: October 24, 2012
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Research on spatial localization method of composite damage under strong noise
Zhongyan Jin1, Qihong Zhou1, Zeguang Pei1
1College of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Ultrasonics
|March 24, 2024
Summary
This study introduces a new method for damage spatial imaging using Lamb waves, improving signal clarity and localization accuracy in noisy environments. The approach enhances signal-to-noise ratio and reduces damage localization errors for composite materials.
Area of Science:
- Structural Health Monitoring
- Non-Destructive Testing
- Materials Science
Background:
- Lamb wave-based structural health monitoring is crucial for detecting damage in composite materials.
- Strong ambient noise significantly degrades the performance of Lamb wave signal processing and damage localization.
- Accurate spatial imaging of damage is essential for effective structural integrity assessment.
Purpose of the Study:
- To develop a robust damage spatial imaging approach for Lamb wave signals corrupted by strong noise.
- To enhance the signal-to-noise ratio (SNR) and improve the accuracy of damage localization.
- To enable reliable detection and spatial mapping of damage in composite structures.
Main Methods:
- Variable Mode Decomposition (VMD) optimized by improved Grey Wolf optimization (IGWO) for signal decomposition.
- Correlation coefficient-based selection of optimal modal components and residuals for signal reconstruction.
- Enhanced Discrete Wavelet Transform (DWT) utilizing Shannon entropy for adaptive denoising.
- Damage spatial localization model integrating the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) and Convolutional Neural Networks (CNN).
Main Results:
- Successfully increased the signal-to-noise ratio (SNR) of the reconstructed Lamb wave response signals.
- Significantly reduced the spatial localization error of damage under strong noise conditions.
- Demonstrated effective damage spatial imaging and localization in experimental validation.
Conclusions:
- The proposed novel signal extraction and spatial imaging method effectively addresses challenges posed by strong noise in Lamb wave-based damage localization.
- The integrated approach of VMD, DWT, RAPID, and CNN offers a promising solution for structural health monitoring of composite materials.
- This research expands the capability of Lamb wave techniques for reliable damage assessment in adverse noisy environments.
