Abstract
Several industries use non-destructive testing (NDT) methods to check the properties of parts and structures for flaws and oddities without affecting the part's stability or causing damage to the part being checked. It involves surveillance. Situation of the materials (Material State Awareness (MSA)) and the structural health monitoring (SHM). Using NDT procedures can help eliminate potential losses and risks associated with component failures while reducing both money and time by not sacrificing its reliability and upcoming utilization. On the other hand, machine learning (ML) and artificial intelligence (AI) techniques are practical instruments that can aid in automated data collection and analysis, offering fresh insights and perhaps enhancing detection efficiency at a high cost quickly and easily. The present research provides an overview of modern AI-ML NDT algorithms and their applications of associated with smart technologies, such as digital twins and machine vision (MV).
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
