arXiv Machine Learning June 5, 2026 By Nehal Afifi, Abdelmonem Elhendawi, Felix Leitenberger, Nadine Piat, Sven Matthiesen

Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencoder

Read the original on arXiv Machine Learning →

arXiv:2606. 05274v1 Announce Type: new Abstract: Electro-Hydrostatic Actuators (EHAs) are widely used in aerospace and industrial systems, where timely detection of sensor anomalies is essential to ensure safe and reliable operation.

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