Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance

Infrastructure maintenance is critical to ensuring public safety and the longevity of essential structures. Nondestructive Evaluation (NDE) techniques allow for infrastructure inspection without causing damage. Computer vision has emerged as a powerful tool in this domain, providing automated, effic...

Full description

Saved in:
Bibliographic Details
Main Authors: Samira Mohammadi, Sasan Sattarpanah Karganroudi, Vahid Rahmanian
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Machines
Subjects:
Online Access:https://www.mdpi.com/2075-1702/13/1/11
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832588050276810752
author Samira Mohammadi
Sasan Sattarpanah Karganroudi
Vahid Rahmanian
author_facet Samira Mohammadi
Sasan Sattarpanah Karganroudi
Vahid Rahmanian
author_sort Samira Mohammadi
collection DOAJ
description Infrastructure maintenance is critical to ensuring public safety and the longevity of essential structures. Nondestructive Evaluation (NDE) techniques allow for infrastructure inspection without causing damage. Computer vision has emerged as a powerful tool in this domain, providing automated, efficient, and accurate solutions for defect detection, structural monitoring, and real-time analysis. This review explores the current state of computer vision in NDE, discussing key techniques, applications across various infrastructure types, and the integration of deep learning models such as convolutional neural networks (CNNs), vision transformers (ViTs), and hybrid models. The review also highlights challenges, including data availability and scalability. It proposes future research directions, including real-time monitoring and the integration of Artificial Intelligence (AI) with Internet of Things (IoT) devices for comprehensive inspections.
format Article
id doaj-art-38fbd2db697e4e1196afe352b5c91f6a
institution Kabale University
issn 2075-1702
language English
publishDate 2024-12-01
publisher MDPI AG
record_format Article
series Machines
spelling doaj-art-38fbd2db697e4e1196afe352b5c91f6a2025-01-24T13:39:07ZengMDPI AGMachines2075-17022024-12-011311110.3390/machines13010011Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure MaintenanceSamira Mohammadi0Sasan Sattarpanah Karganroudi1Vahid Rahmanian2Centre National Intégré du Manufacturier Intelligent, Université du Québec à Trois-Rivières, 575 Boul de l’Université, Drummondville, QC J2C 0R5, CanadaCentre National Intégré du Manufacturier Intelligent, Université du Québec à Trois-Rivières, 575 Boul de l’Université, Drummondville, QC J2C 0R5, CanadaCentre National Intégré du Manufacturier Intelligent, Université du Québec à Trois-Rivières, 575 Boul de l’Université, Drummondville, QC J2C 0R5, CanadaInfrastructure maintenance is critical to ensuring public safety and the longevity of essential structures. Nondestructive Evaluation (NDE) techniques allow for infrastructure inspection without causing damage. Computer vision has emerged as a powerful tool in this domain, providing automated, efficient, and accurate solutions for defect detection, structural monitoring, and real-time analysis. This review explores the current state of computer vision in NDE, discussing key techniques, applications across various infrastructure types, and the integration of deep learning models such as convolutional neural networks (CNNs), vision transformers (ViTs), and hybrid models. The review also highlights challenges, including data availability and scalability. It proposes future research directions, including real-time monitoring and the integration of Artificial Intelligence (AI) with Internet of Things (IoT) devices for comprehensive inspections.https://www.mdpi.com/2075-1702/13/1/11nondestructive evaluationstructural health monitoringdefect detectiondeep learning modelspredictive maintenance
spellingShingle Samira Mohammadi
Sasan Sattarpanah Karganroudi
Vahid Rahmanian
Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
Machines
nondestructive evaluation
structural health monitoring
defect detection
deep learning models
predictive maintenance
title Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
title_full Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
title_fullStr Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
title_full_unstemmed Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
title_short Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
title_sort advancements in smart nondestructive evaluation of industrial machines a comprehensive review of computer vision and ai techniques for infrastructure maintenance
topic nondestructive evaluation
structural health monitoring
defect detection
deep learning models
predictive maintenance
url https://www.mdpi.com/2075-1702/13/1/11
work_keys_str_mv AT samiramohammadi advancementsinsmartnondestructiveevaluationofindustrialmachinesacomprehensivereviewofcomputervisionandaitechniquesforinfrastructuremaintenance
AT sasansattarpanahkarganroudi advancementsinsmartnondestructiveevaluationofindustrialmachinesacomprehensivereviewofcomputervisionandaitechniquesforinfrastructuremaintenance
AT vahidrahmanian advancementsinsmartnondestructiveevaluationofindustrialmachinesacomprehensivereviewofcomputervisionandaitechniquesforinfrastructuremaintenance