Model-Based Parametric Study of Surface-Breaking Defect Characterization Using Half-Skip Total Focusing Method
Journal article, 2023

As the demand of structural integrity in manufacturing industries is increasing, the ultrasonic array technique has drawn more attention thanks to its inspection flexibility and versatility. By taking advantage of the possibility of individual triggering of each array element, full matrix capture (FMC) data acquisition strategy has been developed that contains the entire information of an inspection scenario. Total focusing method (TFM) as one of the ultrasonic imaging algorithms, is preferably applied to FMC dataset since it uses all information in FMC to synthetically focus the sound energy at every image pixel in the region of interest. Half-skip TFM (HSTFM) is proposed in multi-mode TFM imaging that involves a backwall reflection wave path, so that the defect profile could be reconstructed for accurate defect characterization. In this paper, a method involving Snell’s law-based wave mode conversion is proposed to account for more reasonable wave propagation time when wave mode conversion happens at backwall reflection in HSTFM. A series of model based simulations (in software simSUNDT) are performed for parametric studies, with the intention of investigating the capability of defect characterization using HSTFM with varying tilt angle and relative position of surface-breaking notch to array probe. The results show that certain TFM modes could help with defect characterization, but the effectiveness is limited with varying defect features. It is inappropriate to address a certain mode for all characterization perspectives but rather a combination, i.e., multi-mode TFM, should be adopted for possible interpretation and characterization of defect features.

Defect characterization

Ultrasonic array

Simulation

Total focusing method

simSUNDT

Author

Xiangyu Lei

Chalmers, Industrial and Materials Science, Engineering Materials

Håkan Wirdelius

University West

Johan E. Carlson

Luleå University of Technology

Journal of Nondestructive Evaluation

01959298 (ISSN) 15734862 (eISSN)

Vol. 42 2 37

Subject Categories

Other Physics Topics

Fluid Mechanics and Acoustics

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing

DOI

10.1007/s10921-023-00949-7

More information

Latest update

5/9/2023 1