Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 9th European Workshop on Structural Health Monitoring (EWSHM 2018) |
| Publikationsstatus | Veröffentlicht - 2018 |
| Veranstaltung | 9th European Workshop on Structural Health Monitoring, EWSHM 2018 - Manchester, Großbritannien / Vereinigtes Königreich Dauer: 10 Juli 2018 → 13 Juli 2018 |
Abstract
When operating a wind turbine, damage of rotor blades is a serious problem which has to be taken into account. The position of the damage is an important information which is connected with the damage significance. Therefore a monitoring system which estimates the position helps to make better decisions for maintenance and repairing. One promising approach for detection and localization of damages in early stages are acoustic emission (AE) methods which detect and localize damage events. In contrast to most AE approaches which require about 12 to 40 sensors, we propose to use the airborne sound in lower frequencies up to about 30 kHz with only three fiber optical microphones. Based on this approach a damage localization algorithm was developed which uses time differences of arrival (TDOA) of the damage signals from microphones which are placed at different positions inside the blade. The localization algorithm estimates in which part of the blade the damage occurred and the distance to the root of the blade. The localization results of seven damage events, which happened during a fatigue test of a 34m rotor blade are presented. An average distance error of about 1.4m for the damage event localization was achieved.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
- Ingenieurwesen (insg.)
- Architektur
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9th European Workshop on Structural Health Monitoring (EWSHM 2018). 2018.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Acoustic Emission Localization Using Airborne Sound
T2 - 9th European Workshop on Structural Health Monitoring, EWSHM 2018
AU - Krause, Thomas
AU - Ostermann, Jörn
N1 - Publisher Copyright: © 2018 NDT.net. All rights reserved.
PY - 2018
Y1 - 2018
N2 - When operating a wind turbine, damage of rotor blades is a serious problem which has to be taken into account. The position of the damage is an important information which is connected with the damage significance. Therefore a monitoring system which estimates the position helps to make better decisions for maintenance and repairing. One promising approach for detection and localization of damages in early stages are acoustic emission (AE) methods which detect and localize damage events. In contrast to most AE approaches which require about 12 to 40 sensors, we propose to use the airborne sound in lower frequencies up to about 30 kHz with only three fiber optical microphones. Based on this approach a damage localization algorithm was developed which uses time differences of arrival (TDOA) of the damage signals from microphones which are placed at different positions inside the blade. The localization algorithm estimates in which part of the blade the damage occurred and the distance to the root of the blade. The localization results of seven damage events, which happened during a fatigue test of a 34m rotor blade are presented. An average distance error of about 1.4m for the damage event localization was achieved.
AB - When operating a wind turbine, damage of rotor blades is a serious problem which has to be taken into account. The position of the damage is an important information which is connected with the damage significance. Therefore a monitoring system which estimates the position helps to make better decisions for maintenance and repairing. One promising approach for detection and localization of damages in early stages are acoustic emission (AE) methods which detect and localize damage events. In contrast to most AE approaches which require about 12 to 40 sensors, we propose to use the airborne sound in lower frequencies up to about 30 kHz with only three fiber optical microphones. Based on this approach a damage localization algorithm was developed which uses time differences of arrival (TDOA) of the damage signals from microphones which are placed at different positions inside the blade. The localization algorithm estimates in which part of the blade the damage occurred and the distance to the root of the blade. The localization results of seven damage events, which happened during a fatigue test of a 34m rotor blade are presented. An average distance error of about 1.4m for the damage event localization was achieved.
UR - http://www.scopus.com/inward/record.url?scp=85070883866&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85070883866
BT - 9th European Workshop on Structural Health Monitoring (EWSHM 2018)
Y2 - 10 July 2018 through 13 July 2018
ER -