scholarly journals Automatic defect localization and characterization through machine learning based inversion for guided wave imaging in SHM

2019 ◽  
Author(s):  
Roberto Miorelli ◽  
Andrii Kulakovskyi ◽  
Olivier Mesnil ◽  
Oscar d’Almeida
Keyword(s):  
Machine Learning ◽  
Guided Wave ◽  
Defect Localization ◽  
Wave Imaging

scholarly journals Synthetic aperture guided wave imaging using a mobile sensor platform

2012 ◽  
Author(s):  
Gordon Dobie ◽  
Walter Galbraith ◽  
Charles MacLeod ◽  
Rahul Summan ◽  
Gareth Pierce
Keyword(s):  
Guided Wave ◽  
Synthetic Aperture ◽  
Mobile Sensor ◽  
Sensor Platform ◽  
Wave Imaging

Early Fatigue Damage Evaluation of Nonlinear Guided Wave Imaging in Hyperelastic Materials

2021 ◽  
Author(s):  
Chengwei Zhao ◽  
Sunia Tanweer ◽  
Jian Li ◽  
Min Lin ◽  
Xiang Zhang ◽  
...  
Keyword(s):  
Fatigue Damage ◽  
Guided Waves ◽  
Lamb Waves ◽  
Tone Burst ◽  
Guided Wave ◽  
Third Order ◽  
Hyperelastic Materials ◽  
Third Order Elastic Constants ◽  
Wave Imaging ◽  
Processing Platform

Abstract Nonlinear ultrasonic guided waves have superior sensitivity of the early fatigue damage. This paper investigates the analysis of the second harmonics of Lamb waves in a free boundary aluminum plate, and the internal resonance conditions between the Lamb wave primary modes and the second harmonics. The Murnaghan’s model is implemented in a finite element (FE) analysis to describe the hyperelastic constitutive relation for nonlinear acoustic modeling. The second harmonics of s0 mode are actuated by a 60kHz Hanning-windowed tone burst. A guided wave signal processing platform is developed for tomographic imaging. The different stages of fatigue are reflected by the changes of third-order elastic constants (TOECs) in Murnaghan’s model. The reconstructed damage locations match well with the actual ones cross different degrees and depths of fatigue.

Ultrasonic guided wave imaging with deep learning: Applications in corrosion mapping

2022 ◽  
Vol 169 ◽  
pp. 108761
Author(s):  
Xiaocen Wang ◽  
Min Lin ◽  
Jian Li ◽  
Junkai Tong ◽  
Xinjing Huang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Guided Wave ◽  
Ultrasonic Guided Wave ◽  
Wave Imaging

Theory and Methodology of Electromagnetic Ultrasonic Guided Wave Imaging

2020 ◽  
Author(s):  
Songling Huang ◽  
Yu Zhang ◽  
Zheng Wei ◽  
Shen Wang ◽  
Hongyu Sun
Keyword(s):  
Guided Wave ◽  
Ultrasonic Guided Wave ◽  
Wave Imaging

scholarly journals Machine learning at the interface of structural health monitoring and non-destructive evaluation

2020 ◽  
Vol 378 (2182) ◽  
pp. 20190581
Author(s):  
P. Gardner ◽  
R. Fuentes ◽  
N. Dervilis ◽  
C. Mineo ◽  
S.G. Pierce ◽  
...  
Keyword(s):  
Machine Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ultrasonic Inspection ◽  
Guided Wave ◽  
Structural Health ◽  
Non Destructive Evaluation ◽  
Ultrasonic Guided Wave ◽  
Detection And Identification ◽  
Non Destructive

While both non-destructive evaluation (NDE) and structural health monitoring (SHM) share the objective of damage detection and identification in structures, they are distinct in many respects. This paper will discuss the differences and commonalities and consider ultrasonic/guided-wave inspection as a technology at the interface of the two methodologies. It will discuss how data-based/machine learning analysis provides a powerful approach to ultrasonic NDE/SHM in terms of the available algorithms, and more generally, how different techniques can accommodate the very substantial quantities of data that are provided by modern monitoring campaigns. Several machine learning methods will be illustrated using case studies of composite structure monitoring and will consider the challenges of high-dimensional feature data available from sensing technologies like autonomous robotic ultrasonic inspection. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

The feasibility of synthetic aperture guided wave imaging to a mobile sensor platform

2013 ◽  
Vol 58 ◽  
pp. 10-17 ◽  
Author(s):  
Gordon Dobie ◽  
S. Gareth Pierce ◽  
Gordon Hayward
Keyword(s):  
Guided Wave ◽  
Synthetic Aperture ◽  
Mobile Sensor ◽  
Sensor Platform ◽  
Wave Imaging

Multi-Helical Path Exploitation in Sparsity-Based Guided-Wave Imaging of Defects in Pipes

2018 ◽  
Vol 37 (2) ◽  
Author(s):  
A. Golato ◽  
F. Ahmad ◽  
S. Santhanam ◽  
M. G. Amin
Keyword(s):  
Guided Wave ◽  
Wave Imaging
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