A methodology for evaluating detection performance of ultrasonic array imaging algorithms for coarse-grained...

Area of Science:

• Materials Science
• Non-Destructive Testing
• Ultrasonic Imaging

Background:

• Coarse-grained metals in power plants require advanced inspection techniques.
• Conventional ultrasound methods struggle with grain scattering noise, limiting defect detection.
• Array probes and full matrix capture (FMC) imaging offer potential improvements.

Purpose of the Study:

• To propose a robust methodology for evaluating ultrasonic imaging algorithm performance.
• To quantify the detection performance using probability of detection (POD) and probability of false alarm (PFA).
• To illustrate the methodology using three FMC algorithms on a representative material sample.

Main Methods:

• Development of a statistical methodology to assess imaging algorithm performance.
• Application of the methodology to three FMC algorithms: Total Focusing Method (TFM), Phase-Coherent Imaging (PCI), and Decomposition of the Time-Reversal Operator with Multiple Scattering Filter (DORT MSF).
• Data acquisition using 64-element array probes (1 and 5 MHz) on a coarse-grained nickel super alloy sample with artificial defects, in pulse-echo mode.

Main Results:

• The proposed methodology successfully quantifies detection performance via POD and PFA.
• Initial application to TFM, PCI, and DORT MSF algorithms on the test sample showed similar flaw detection capabilities.
• The study focused on illustrating the methodology, not a comprehensive algorithm comparison.

Conclusions:

• A validated methodology exists for evaluating ultrasonic imaging algorithms for coarse-grained metals.
• The tested FMC algorithms demonstrated comparable performance in this specific experimental setup.
• Further investigation is needed to compare algorithm performance across a wider range of conditions and materials.