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Fast frequency-domain symbolic coherence total focusing method for array electromagnetic acoustic transducer
Zongjian Zhang1, Zhengguo Fu2, Yang Zheng3
1College of Mechanical and Energy Engineering, Beijing University of Technology, Beijing 100124, China; China Special Equipment Inspection and Research Institute, Beijing 100029, China.
This study introduces a fast frequency-domain imaging algorithm for array electromagnetic acoustic transducers (EMATs). The advanced method enhances non-destructive testing (NDT) by providing high-resolution defect detection with reduced computation time.
Area of Science:
- Materials Science
- Engineering
- Physics
Background:
- Array-based non-destructive testing (NDT) offers improved inspection efficiency and supports intelligent systems.
- Electromagnetic acoustic transducers (EMATs) provide non-contact inspection, ideal for coated or high-temperature materials.
- Array EMATs enhance imaging resolution and defect characterization.
Purpose of the Study:
- To develop a fast frequency-domain imaging algorithm for array EMATs.
- To improve defect detection clarity and reduce computational complexity in NDT.
- To validate the algorithm's performance for on-line inspection applications.
Main Methods:
- Full matrix capture data from array EMATs was utilized.
- A frequency-domain signed coherence total focusing method was developed, based on wave equation solutions.
- Techniques including double-square-root vertical wavenumber, frequency-domain zero-padding, time-domain interpolation, Gaussian filtering, and signed coherence factor were employed.
Main Results:
- The developed algorithm achieved an effective detection depth of 75 mm.
- Single image computation time was reduced to approximately 0.59 seconds.
- High-contrast, high-spatial-resolution detection of multiple and adjacent defects was demonstrated.
Conclusions:
- The array EMAT integrated with the proposed frequency-domain algorithm shows significant potential for on-line NDT.
- The method offers clearer imaging and efficient defect characterization compared to traditional time-domain approaches.
- This advancement contributes to more effective automated and intelligent inspection systems.
