Point cloud-based elastic reverse time migration for ultrasonic imaging of components with vertical surfaces

Jing Rao, Jilai Wang, Stefan Kollmannsberger, Jianfeng Shi, Hailing Fu*, Ernst Rank

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

This work presents a new ultrasonic imaging framework for non-destructive evaluation of components with vertical or steeply dipping surfaces and demonstrates its ability of accurately characterizing multiple defects hidden in the interior of the component based on a limited coverage of ultrasonic linear phased array. Central to the framework is a point cloud-based elastic reverse time migration (PC-based ERTM) method. First, a surface reconstruction is derived from the point cloud provided through photos of an object from multiple views by bundle adjustment. Second, by taking the surface reconstruction as a geometric background estimate for elastic reverse time migration, the algorithm considers information of multiple scattering and mode conversions as well as multiple wave reflections from the component's bottom and aims at detecting internal defects. The effectiveness and accuracy of the PC-based ERTM approach is examined by experiments with multiple defects in extruded aluminum specimens with vertical surfaces. Experimental results show that notches and side-drilled holes in components can be reconstructed accurately.

Original languageEnglish
Article number108144
JournalMechanical Systems and Signal Processing
Volume163
DOIs
Publication statusPublished - 15 Jan 2022
Externally publishedYes

Keywords

  • Elastic reverse time migration
  • Image-based surface reconstruction
  • Point cloud
  • Ultrasonic imaging
  • Vertical surface

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