Application Research of Ultrasonic-Guided Wave Technology in Pipeline Corrosion Defect Detection: A Review

Исследование применения технологии ультразвуковых направляемых волн для обнаружения коррозионных дефектов трубопроводов: обзор
Feng Lyu, Xinyue Zhou, Zheng Ding, Xinglong Qiao, Dan Song
2024-03-18

Lamb wavesnon-destructive testingpipeline corrosion detectionshear horizontal wavesultrasonic-guided wave technology
This paper presents research on the application of ultrasonic-guided wave technology in corrosion defect identification, expounds the relevant ultrasonic-guided wave theories and the principle of ultrasonic-guided wave non-destructive testing of pipelines, and discusses the Lamb wave and shear horizontal wave mode selection that is commonly used in ultrasonic-guided wave corrosion detection. Furthermore, research progress in the field of ultrasonic-guided wave non-destructive testing (NDT) technology, i.e., regarding transducers, structural health monitoring, convolutional neural networks, machine learning, and other fields, is reviewed. Finally, the future prospects of ultrasonic-guided wave NDT technology are discussed.
1
Future development prospects for ultrasonic-guided wave nondestructive testing technology are discussed.
2
It explains relevant guided-wave theory and the operating principles of ultrasonic-guided wave pipeline inspection.
3
Research progress is summarized across transducers, structural health monitoring, convolutional neural networks, and machine learning.
4
The paper reviews ultrasonic-guided wave technology for identifying corrosion defects in pipelines using nondestructive testing.
5
The review examines selection of Lamb and shear horizontal wave modes commonly used for corrosion detection.

Pipeline corrosion defects

Ultrasonic-guided wave non-destructive detection and identification of pipeline corrosion defects, including wave-mode selection, transducers, structural health monitoring, and machine-learning-based analysis

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Publication Date
2024-03-18
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Authors
Feng Lyu
Xinyue Zhou
Zheng Ding
Xinglong Qiao
Dan Song
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