Machine Learning-Enriched Lamb Wave Approaches for Automated Damage Detection

• Published in: Sensors (Basel, Switzerland) Vol. 20; no. 6; p. 1790
• Main Authors: Zhang, Zi, Pan, Hong, Wang, Xingyu, Lin, Zhibin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24.03.2020; MDPI
• Subjects: Algorithms; Artificial intelligence; Automation; Civil engineering; Classification; damage identification; data-driven approach; Datasets; Deep learning; Defects; Knowledge discovery; lamb wave; Machine learning; Methods; Neural networks; Noise; Physical restraints; Physics; Simulation; structural health monitoring; Support vector machines; Wavelet transforms; Lamb wave; structural health monitoring; damage identification; machine learning; data-driven approach

Lamb wave approaches have been accepted as efficiently non-destructive evaluations in structural health monitoring for identifying damage in different states. Despite significant efforts in signal process of Lamb waves, physics-based prediction is still a big challenge due to complexity nature of th...