64893 2025 eng lecture 0 -- -- -- Despite proven approaches available in the literature, structural health monitoring by ultrasonic guided waves under varying environmental and operational conditions is still challenging. The use of machine learning approaches is discussed in this work, considering the complex problem of experimental damage detection under varying load conditions in a composite overwrapped pressure vessel for hydrogen storage. Specifically, unsupervised methods originally developed for image and time series classification are combined with ensemble voting to conceive reliable damage detection technique. This enables the effective combination of the predictions of multiple transducer pairs, even with a limited number of strong individual classifiers. A performance demonstration of the technique is presented using a real damage scenario dataset. 2025 IEEE 12th International Workshop on Metrology for AeroSpace (MetroAeroSpace) Napoli, Italy 18.06.2025 20.06.2025 0 publish false true Vittorio Memmolo eng uncontrolled Structural Health Monitoring eng uncontrolled Guided Ultrasonic Waves Angewandte Physik 8 Zerstörungsfreie Prüfung 8.4 Akustische und elektromagnetische Verfahren Energie Datei im Netzwerk der BAM verfügbar ("Closed Access") Präsentation Wasserstoff