Adaptive TFM imaging with multi-stage channel optimization for enhanced defect characterization in coarse-grained...

Area of Science:

• Materials Science
• Engineering
• Physics

Background:

• Ultrasonic non-destructive testing (NDT) faces challenges in inspecting small or inclined cracks due to signal attenuation and scattering.
• Accurate defect detection and characterization are crucial for material integrity assessment.

Purpose of the Study:

• To develop an adaptive Total Focusing Method (TFM) that enhances signal-to-noise ratio (SNR) and improves defect characterization robustness.
• To address limitations in inspecting subwavelength and steeply inclined cracks in polycrystalline materials.

Main Methods:

• Proposed an adaptive TFM approach featuring an optimized baseline subtraction scheme for defect localization.
• Implemented a hierarchical channel optimization process, Multi-Step Channel Optimization TFM (MSCO-TFM), over receivers, transmitters, and A-scan channels.
• Validated the method through numerical simulations and experimental evaluations using SNR and 6-dB sizing metrics.

Main Results:

• MSCO-TFM demonstrated superior detection and characterization performance compared to conventional TFM and receiver-optimized TFM (ROTFM).
• Achieved an average SNR improvement of 9.78 dB over conventional TFM.
• Showcased excellent characterization accuracy for challenging defects, including a 5 mm, 45° crack.

Conclusions:

• MSCO-TFM offers a robust and effective solution for ultrasonic NDT of challenging defects without requiring extensive prior knowledge or training data.
• The method directly optimizes acquired data, compensating for misalignments and proving suitable for practical engineering applications.
• MSCO-TFM presents a significant advancement in ultrasonic defect characterization, enhancing reliability and applicability.