This research demonstrates stress corrosion cracking detection in steel using AI-integrated ultrasonic testing, indicating advancements in structural health monitoring.
Recent trends in the field of structural integrity highlight the integration of Artificial Intelligence (AI) with related domains such as Structural Health Monitoring (SHM), Non-Destructive Evaluation (NDE), and the assessment of Stress Corrosion Cracking (SCC). AI plays a pivotal role in developing intelligent solutions to complex challenges, particularly in the detection and characterization of SCC. While several techniques are available, this paper focuses on the Ultrasonic Testing (UT) based Non-Destructive Testing (NDT) method integrated with Artificial Intelligence (AI), making it a robust Industry 4.0 solution. Deep learning, a subset of Artificial Intelligence and Machine Learning, is already considered as a key technology in Industry 4.0 solutions. This paper discusses the detection of SCC in steel using UT based data and deep learning. The trained neural network model will be used for the detection of SCC in the steel.
No takes yet. Share an insight, caveat, or question.
Rai et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: