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From Sound to Vision: Applying Beamforming to Reduce Parasitic Noise Applying Beamforming to Reduce Parasitic Noise for Fault Detectionfor Fault Detection

Steinhoff, Leon and Koschlik, Ann-Kathrin and Soria-Gomez, Maria and Arts, Emy and Kunz, Veit Dominik and Raddatz, Florian and Wende, Gerko (2023) From Sound to Vision: Applying Beamforming to Reduce Parasitic Noise Applying Beamforming to Reduce Parasitic Noise for Fault Detectionfor Fault Detection. DAGA 2023 - 49. Jahrestagung für Akustik, 06.-09. März 2023, 06-09.03.2023, Hamburg, Germany.

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Abstract

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 [1 acoustics. Previous studies [1 --4] with single microphones 4] with single microphones showed first results for UAS but lacked robustness regarding showed first results for UAS but lacked robustness regarding environmental noise.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. algorithm aiming for improved accuracy.

Item URL in elib:https://elib.dlr.de/197204/
Document Type:Conference or Workshop Item (Poster)
Title:From Sound to Vision: Applying Beamforming to Reduce Parasitic Noise Applying Beamforming to Reduce Parasitic Noise for Fault Detectionfor Fault Detection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Steinhoff, LeonGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Koschlik, Ann-KathrinGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Soria-Gomez, MariaGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Arts, EmyGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Kunz, Veit DominikHAW Hamburg, Berliner Tor 5, 20099 HamburgUNSPECIFIEDUNSPECIFIED
Raddatz, FlorianGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Wende, GerkoGerman Aerospace Center (DLR), Institute for Maintenance, Repair and Overhaul, Hein--SaßSaß--WegWeg22, 21129 Hamburg22, 21129 HamburgUNSPECIFIEDUNSPECIFIED
Date:March 2023
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Acoustic Monitoring, CBM, UAV, Fault Detection
Event Title:DAGA 2023 - 49. Jahrestagung für Akustik, 06.-09. März 2023
Event Location:Hamburg, Germany
Event Type:national Conference
Event Dates:06-09.03.2023
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:Digitalisation
DLR - Program:D - no assignment
DLR - Research theme (Project):D - no assignment
Location: Hamburg
Institutes and Institutions:Institute of Maintenance, Repair and Overhaul
Deposited By: Koschlik, Ann-Kathrin
Deposited On:12 Sep 2023 07:39
Last Modified:12 Sep 2023 07:39

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