Applying Beamforming to Reduce Parasitic Noise for Fault Detectionfor Fault Detection

Kurzfassung

The propeller blades of unmanned aircraft systems (UAS) are prone to damage and wear and tear, which can cause prone to damage and wear and tear, which can cause mechanical stress on the components, performance mechanical stress on the components, performance degradation and a decreased flight stability. The aim is to degradation and a decreased flight stability. The aim is to automate the maintenance process of the propeller blades automate the maintenance process of the propeller blades without the need of interacting with the UAS by means of without the need of interacting with the UAS by means of acoustics. Previous studies with with single microphones showed first results for UAS but lacked robustness regarding showed first results for UAS but lacked robustness regarding environmental noise. This approach often fails when used laboratory conditions. This approach often fails when used in noisy environments like an openin noisy environments like an open--air field. Our new approach deploys multiple microphones and a new approach deploys multiple microphones and a new algorithm aiming for improved accuracy.