Towards a multi-fidelity deep learning framework for a fast and realistic generation of ultrasonic multi-modal Total Focusing Method images in complex geometries

GE Granados, R Miorelli, F Gatti, S Robert… - NDT & E …, 2023 - Elsevier
This paper presents a deep-learning surrogate model tailored for a fast generation of
realistic ultrasonic images in the Multi-modal Total Focusing Method (M-TFM) framework …

A physics-embedded deep-learning framework for efficient multi-fidelity modeling applied to guided wave based structural health monitoring

V Nerlikar, R Miorelli, A Recoquillay, O d'Almeida - Ultrasonics, 2024 - Elsevier
Health monitoring of structures using ultrasonic guided waves is an evolving technology with
potential applications in monitoring pipelines, civil bridges, and aircraft components …

Quantifying predictive uncertainty in damage classification for nondestructive evaluation using Bayesian approximation and deep learning

Z Li, Y Deng - Inverse Problems, 2024 - iopscience.iop.org
Magnetic flux leakage (MFL), a widely used nondestructive evaluation (NDE) method, for
inspecting pipelines to prevent potential long-term failures. However, during field testing …

Pulse-modulation eddy current imaging for 3D profile reconstruction of subsurface corrosion in metallic structures of aviation

B Yan, Y Li, Z Liu, S Ren, Z Chen, X Lü… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Metallic structures of non-ferromagnetic materials such as aluminum alloy, titanium alloy,
etc., are widely used in the engineering field of aviation. Owing to harsh and hostile …

A deep learning framework for efficient global sensitivity analysis and shap values calculations applied to eddy current testing problems

GE Granados, R Miorelli, F Gatti… - … Annual Review of …, 2023 - asmedigitalcollection.asme.org
In the context of the nondestructive testing and evaluation research community, global
sensitivity analysis (GSA) methods are widespread tools for quantifying the sensitivity of …

Bayesian data fusion of eddy current testing for flaw characterization with uncertainty evaluation

T Tomizawa, N Yusa - NDT & E International, 2024 - Elsevier
This study proposed a data fusion method based on Bayesian estimation for flaw
characterization using eddy current signals and evaluated its applicability using measured …

Machine Learning-Based Digital Twin Framework for Realistic Guided Wave Signal Generation, Applied to Reliability Assessment and Global Sensitivity Analysis in …

V Nerlikar, R Miorelli… - … Annual Review of …, 2023 - asmedigitalcollection.asme.org
An ultrasonic guided wave-based structural health monitoring system has potential
applications in mainy domains such as, the oil and gas industry, civil engineering, and …

Exploring high-frequency eddy-current testing for sub-aperture defect characterisation using parametric-manifold mapping

RR Hughes, BW Drinkwater - NDT & E International, 2021 - Elsevier
Accurate characterisation of small defects remains a challenge in non-destructive testing
(NDT). In this paper, a principle-component parametric-manifold mapping approach is …

Design of eddy current and capacitance dual-mode sensor for thickness detection of thermal barrier coatings

W Fan, L Wang - Measurement Science and Technology, 2024 - new.iopscience.iop.org
Thermal barrier coatings (TBCs) can markedly enhance the service temperature of high-
temperature alloys, thereby enhancing the engine thrust-to-weight ratio. However, TBCs …

New Proposal for Inverse Algorithm Enhancing Noise Robust Eddy-Current Non-Destructive Evaluation

M Smetana, L Behun, D Gombarska, L Janousek - Sensors, 2020 - mdpi.com
Solution of inverse problem in eddy-current non-destructive evaluation of material defects is
concerned in this study. A new inverse algorithm incorporating three methods is proposed …