[HTML][HTML] Automated detection of corrosion in used nuclear fuel dry storage canisters using residual neural networks

T Papamarkou, H Guy, B Kroencke, J Miller… - Nuclear Engineering …, 2021 - Elsevier
Nondestructive evaluation methods play an important role in ensuring component integrity
and safety in many industries. Operator fatigue can play a critical role in the reliability of such …

Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection

DJ Atha, MR Jahanshahi - Structural Health Monitoring, 2018 - journals.sagepub.com
Corrosion is a major defect in structural systems that has a significant economic impact and
can pose safety risks if left untended. Currently, an inspector visually assesses the condition …

Automated defect recognition on X-ray radiographs of solid propellant using deep learning based on convolutional neural networks

D Gamdha, S Unnikrishnakurup, KJJ Rose… - Journal of …, 2021 - Springer
For defense applications, rapid X-ray inspection of propellant samples is essential for the
identification and assessment of defects. Automation of this process using artificial …

Machine learning-aided damage identification of mock-up spent nuclear fuel assemblies in a sealed dry storage canister

B Zhuang, A Arcaro, B Gencturk, R Ghanem - Engineering Applications of …, 2024 - Elsevier
Spent nuclear fuel (SNF) assemblies (FAs) contain high-level radioactive waste from
operation of nuclear power plants (NPPs). Their safe storage in dry casks is critical for …

An end-to-end framework for shipping container corrosion defect inspection

Z Bahrami, R Zhang, T Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The worldwide transportation industry relies heavily on shipping containers.
Containerization has made it easier to transfer goods all over the world by guaranteeing …

[HTML][HTML] Autonomous Image-Based Corrosion Detection in Steel Structures Using Deep Learning

A Das, S Dorafshan, N Kaabouch - Sensors, 2024 - mdpi.com
Steel structures are susceptible to corrosion due to their exposure to the environment.
Currently used non-destructive techniques require inspector involvement. Inaccessibility of …

Inferring the operational status of nuclear facilities with convolutional neural networks to support international safeguards verification

ZN Gastelum, TM Shead - Journal of Nuclear Materials …, 2018 - ingentaconnect.com
International nuclear safeguards analysts use images in myriad ways to support verification
analysis tasks, from analyzing the design and construction of a facility to understanding the …

Corrosion and coating defect assessment of coal handling and preparation plants (CHPP) using an ensemble of deep convolutional neural networks and decision …

Y Yu, AN Hoshyar, B Samali, G Zhang… - Neural Computing and …, 2023 - Springer
In view of the problems of ineffective feature extraction and low detection accuracy in
existing detection system, this study presents a novel machine vision-based approach …

[HTML][HTML] Aircraft fuselage corrosion detection using artificial intelligence

B Brandoli, AR de Geus, JR Souza, G Spadon… - Sensors, 2021 - mdpi.com
Corrosion identification and repair is a vital task in aircraft maintenance to ensure continued
structural integrity. Regarding fuselage lap joints, typically, visual inspections are followed …

Corrosion detection with computer vision and deep learning

A Matthaiou, G Papalambrou… - Developments in the …, 2021 - taylorfrancis.com
This study investigates and test solutions for automated corrosion detection processes that
focus on the visual attributes of corrosion. Corroded surfaces have two visually identified …