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#fault-detection

2 curated events
papersTODAY 04:00 UTC

Machine learning framework targets fault detection in autonomous VTOL aircraft

A new arXiv paper presents a machine learning approach for detecting, isolating, and estimating the severity of faults in autonomous vertical take-off and landing aircraft. The work is motivated by the risk that small component degradations can quickly destabilize multirotor vehicles in safety-critical settings. It aims to provide more robust fault detection and estimation than existing strategies.

safety/aviation/fault-detection/research
papersSEP 10 04:00 UTC

Deep Learning Approach Targets Fault Detection in Aircraft Power Systems

A new arXiv preprint describes a hardware-aware deep learning method for spotting electrical faults and power quality disturbances in More Electric Aircraft. The authors note that most existing diagnostics were built for conventional 50/60 Hz grids and may not transfer to the high-frequency networks used on aircraft. The work aims to support faster, more reliable monitoring of these onboard systems.

deep-learning/aerospace/fault-detection/power-systems