Advancements in Smart Nondestructive Evaluation of Industrial Machines: A Comprehensive Review of Computer Vision and AI Techniques for Infrastructure Maintenance
Samira Mohammadi, Sasan Sattarpanah Karganroudi, Vahid Rahmanian
Abstract
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.