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

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

21 引用 (Scopus)

摘要

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.

源语言英语
文章编号108144
期刊Mechanical Systems and Signal Processing
163
DOI
出版状态已出版 - 15 1月 2022
已对外发布

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