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Ł. Pawlik

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Open access 2026

Anomaly Detection in Vibroacoustic Signals of a DGEN 380 Turbofan Using a LIRA Autoencoder and Gradient Boosting Framework

A hybrid anomaly detection framework for vibroacoustic signals obtained from a DGEN 380 turbofan test bench provides an effective and interpretable solution for anomaly detection in vibroacoustic systems and demonstrates potential for application in predictive maintenance of aeroengines and other rotating machinery.

Ł. Pawlik · IEEE Access · 0 citations