Evaluation of ultrasonic array imaging algorithms for inspection of a coarse grained material

• Published in: AIP conference proceedings Vol. 1581; no. 1
• Main Authors: Van Pamel A, Lowe, M J, Brett, C R
• Format: Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 18.02.2014
• Subjects: Algorithms; Arrays; Electric power generation; False alarms; Flaw detection; Imaging; Inspection; Nickel base alloys; Nondestructive testing; Power plant components; Power plants; Scattering; Superalloys; Ultrasonic testing
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/1.4864815

Improving the ultrasound inspection capability for coarse grain metals remains of longstanding interest to industry and the NDE research community and is expected to become increasingly important for next generation power plants. A test sample of coarse grained Inconel 625 which is representative of future power plant components has been manufactured to test the detectability of different inspection techniques. Conventional ultrasonic A, B, and C-scans showed the sample to be extraordinarily difficult to inspect due to its scattering behaviour. However, in recent years, array probes and Full Matrix Capture (FMC) imaging algorithms, which extract the maximum amount of information possible, have unlocked exciting possibilities for improvements. This article proposes a robust methodology to evaluate the detection performance of imaging algorithms, applying this to three FMC imaging algorithms; Total Focusing Method (TFM), Phase Coherent Imaging (PCI), and Decomposition of the Time Reversal Operator with Multiple Scattering (DORT MSF). The methodology considers the statistics of detection, presenting the detection performance as Probability of Detection (POD) and probability of False Alarm (PFA). The data is captured in pulse-echo mode using 64 element array probes at centre frequencies of 1MHz and 5MHz. All three algorithms are shown to perform very similarly when comparing their flaw detection capabilities on this particular case.