Quantitative Damage Monitoring of Filament Wound Composites by Using Machine Learning-Based Techniques

Composite structures in transportation industries have gained significant attention due to their unique characteristics, including high energy absorption. Non-destructive testing methods coupled with machine learning techniques offer valuable insights into failure mechanisms by analyzing basic parameters. In this study, damage monitoring...

Condition Assessment of Low-Speed Slew Bearings in Offshore Applications Using Acoustic Emission Monitoring

This study presents an approach for the detection of evolving degradation in large-scale low-speed roller bearings by clustering of Acoustic Emission (AE) events, and its application to experimental degradation data. To acquire the latter, a purpose-built linear bearing, representative of a segment of a turret bearing, has been instrumented with...