Details
Originalsprache | Englisch |
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Titel des Sammelwerks | Structural Health Monitoring |
Untertitel | The 9th Asia-Pacific Workshop on Structural Health Monitoring (9APWSHM 2022) |
Herausgeber/-innen | Nik Rajic, Wing Kong Chiu, Martin Veidt, Akira Mita, N. Takeda |
Seiten | 228-235 |
Seitenumfang | 8 |
Publikationsstatus | Veröffentlicht - 30 März 2023 |
Veranstaltung | 9th Asia-Pacific Workshop on Structural Health Monitoring, 9APWSHM 2022 - Cairns, Australien Dauer: 7 Dez. 2022 → 9 Dez. 2022 |
Publikationsreihe
Name | Materials Research Proceedings |
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Band | 27 |
ISSN (Print) | 2474-3941 |
ISSN (elektronisch) | 2474-395X |
Abstract
The human-induced climate change is one of the biggest threats for modern society. Wind energy turbines play a key role in the necessary transformation of the energy sector and their reliable, low-maintenance operation with short downtimes is therefore of particular interest. To this end, automated structural health monitoring (SHM) gained a lot of interest in research and economy. In this work, we propose an algorithm for damage detection in rotor blades using airborne acoustic emissions (AE). Our algorithm inherently uses a localization approach and is therefore not only able to detect a structural damage but also to estimate its position using time differences of arrival (TDoA) of airborne sound waves. Since we intend only an approximate localization of the impulsive damage sounds, we suggest a simple yet effective method based on cross-correlation of energy-envelope functions to estimate the TDoA. For the task of damage detection and localization, only two line-of-sight microphones are required, which makes this approach very economic for SHM. We evaluate our method on two large-scale fatigue tests conducted on a 34-meter and a 30-meter rotor blade under laboratory conditions. During the fatigue tests, we continuously recorded airborne sound signals with multiple microphones placed inside the rotor blades. With our proposed method, we are able to detect and correctly assign the two significant structural damages in both rotor blades to a two-meter-long rotor blade zone without having any false-positive alarms throughout more than 350 hours of continuous audio recordings. Airborne acoustic emissions therefore may be a promising alternative to other conventional monitoring solutions based on structure-borne sound, which usually require considerable denser sensor networks.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
Ziele für nachhaltige Entwicklung
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Structural Health Monitoring: The 9th Asia-Pacific Workshop on Structural Health Monitoring (9APWSHM 2022). Hrsg. / Nik Rajic; Wing Kong Chiu; Martin Veidt; Akira Mita; N. Takeda. 2023. S. 228-235 (Materials Research Proceedings; Band 27).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Localized damage detection in wind turbine rotor blades using airborne acoustic emissions
AU - Lange, Alexander
AU - Hinrichs, Reemt
AU - Ostermann, Jörn
N1 - Funding Information: This research was funded by German Federal Ministry for Economic Affairs and Climate (BMWK) “Multivariate Damage Monitoring of Rotor Blades: Implementation and Analysis of the Effects of Repair Measures” (03EE2043C).
PY - 2023/3/30
Y1 - 2023/3/30
N2 - The human-induced climate change is one of the biggest threats for modern society. Wind energy turbines play a key role in the necessary transformation of the energy sector and their reliable, low-maintenance operation with short downtimes is therefore of particular interest. To this end, automated structural health monitoring (SHM) gained a lot of interest in research and economy. In this work, we propose an algorithm for damage detection in rotor blades using airborne acoustic emissions (AE). Our algorithm inherently uses a localization approach and is therefore not only able to detect a structural damage but also to estimate its position using time differences of arrival (TDoA) of airborne sound waves. Since we intend only an approximate localization of the impulsive damage sounds, we suggest a simple yet effective method based on cross-correlation of energy-envelope functions to estimate the TDoA. For the task of damage detection and localization, only two line-of-sight microphones are required, which makes this approach very economic for SHM. We evaluate our method on two large-scale fatigue tests conducted on a 34-meter and a 30-meter rotor blade under laboratory conditions. During the fatigue tests, we continuously recorded airborne sound signals with multiple microphones placed inside the rotor blades. With our proposed method, we are able to detect and correctly assign the two significant structural damages in both rotor blades to a two-meter-long rotor blade zone without having any false-positive alarms throughout more than 350 hours of continuous audio recordings. Airborne acoustic emissions therefore may be a promising alternative to other conventional monitoring solutions based on structure-borne sound, which usually require considerable denser sensor networks.
AB - The human-induced climate change is one of the biggest threats for modern society. Wind energy turbines play a key role in the necessary transformation of the energy sector and their reliable, low-maintenance operation with short downtimes is therefore of particular interest. To this end, automated structural health monitoring (SHM) gained a lot of interest in research and economy. In this work, we propose an algorithm for damage detection in rotor blades using airborne acoustic emissions (AE). Our algorithm inherently uses a localization approach and is therefore not only able to detect a structural damage but also to estimate its position using time differences of arrival (TDoA) of airborne sound waves. Since we intend only an approximate localization of the impulsive damage sounds, we suggest a simple yet effective method based on cross-correlation of energy-envelope functions to estimate the TDoA. For the task of damage detection and localization, only two line-of-sight microphones are required, which makes this approach very economic for SHM. We evaluate our method on two large-scale fatigue tests conducted on a 34-meter and a 30-meter rotor blade under laboratory conditions. During the fatigue tests, we continuously recorded airborne sound signals with multiple microphones placed inside the rotor blades. With our proposed method, we are able to detect and correctly assign the two significant structural damages in both rotor blades to a two-meter-long rotor blade zone without having any false-positive alarms throughout more than 350 hours of continuous audio recordings. Airborne acoustic emissions therefore may be a promising alternative to other conventional monitoring solutions based on structure-borne sound, which usually require considerable denser sensor networks.
KW - Acoustic Emission
KW - Damage Detection
KW - SHM
KW - Source Localization
KW - TDoA
UR - http://www.scopus.com/inward/record.url?scp=85159594607&partnerID=8YFLogxK
U2 - 10.21741/9781644902455-29
DO - 10.21741/9781644902455-29
M3 - Conference contribution
AN - SCOPUS:85159594607
SN - 9781644902448
T3 - Materials Research Proceedings
SP - 228
EP - 235
BT - Structural Health Monitoring
A2 - Rajic, Nik
A2 - Chiu, Wing Kong
A2 - Veidt, Martin
A2 - Mita, Akira
A2 - Takeda, N.
T2 - 9th Asia-Pacific Workshop on Structural Health Monitoring, 9APWSHM 2022
Y2 - 7 December 2022 through 9 December 2022
ER -