Segmenting hydrogen‐induced cracking defects in steel through scanning acoustic microscopy and deep neural networks

Segmenting hydrogen‐induced cracking defects in steel through scanning acoustic microscopy and deep neural networks

Abstract Hydrogen‐induced cracking (HIC) presents a significant concern in industries, such as oil and gas, petrochemicals, and aerospace, where high‐strength steel is prevalently used. This phenomenon compromises the structural integrity of steel pipelines and equipment. Accurate detection and moni...

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Bibliographic Details
Main Authors: Thi Thu Ha Vu, Tan Hung Vo, Le Hai Tran, Jaeyeop Choi, Truong Tien Vo, Cao Duong Ly, Thanh Phuoc Nguyen, Sudip Mondal, Junghwan Oh
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Engineering Reports
Subjects:
3D reconstruction
deep learning
defect segmentation
hydrogen‐induced cracking
nondestructive testing
Online Access:https://doi.org/10.1002/eng2.12933
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https://doi.org/10.1002/eng2.12933

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