Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | e2520 |
| Fachzeitschrift | Structural Control and Health Monitoring |
| Jahrgang | 27 |
| Ausgabenummer | 5 |
| Frühes Online-Datum | 3 Feb. 2020 |
| Publikationsstatus | Veröffentlicht - 2 Apr. 2020 |
Abstract
When operating a wind turbine, damage of rotor blades is a serious problem. Undetected damages are likely to increase overtime, and therefore, the safety risks and economical burdens also increase. A monitoring system, which detects reliably defects in early stages, gives scope for action and is therefore a key element to avoid damage increase and to optimize the efficiency of wind turbines. One promising approach for damage detection is acoustic emission methods. Although most acoustic emission approaches use ultrasonic sound waves of the structure that require about 12 to 40 sensors to monitor one rotor blade, we propose to use the airborne sound in lower frequencies from about 500 Hz to 35 Hz with three optical microphones and present a signal model-based damage detection algorithm. The real-time algorithm uses six audio features from a spectrogram representation to detect damages and to estimate its significance. In a fatigue test of a 34-m blade, the algorithm detected the damage event and damage increasing without false detection. It was also tested with recordings inside an operating blade of a 3.4-MW wind turbine. In the recorded time period of about 1 year, the algorithm indicated no false detection.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Tief- und Ingenieurbau
- Ingenieurwesen (insg.)
- Bauwesen
- Ingenieurwesen (insg.)
- Werkstoffmechanik
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in: Structural Control and Health Monitoring, Jahrgang 27, Nr. 5, e2520, 02.04.2020.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Damage detection for wind turbine rotor blades using airborne sound
AU - Krause, Thomas
AU - Ostermann, Jörn
N1 - Funding information: This research was funded by German Federal Ministry for Economic Affairs and Energy (BMWi) ?Multivariate Structural Health Monitoring for Rotor Blades? (0324157A). This research was funded by German Federal Ministry for Economic Affairs and Energy (BMWi) “Multivariate Structural Health Monitoring for Rotor Blades” (0324157A).
PY - 2020/4/2
Y1 - 2020/4/2
N2 - When operating a wind turbine, damage of rotor blades is a serious problem. Undetected damages are likely to increase overtime, and therefore, the safety risks and economical burdens also increase. A monitoring system, which detects reliably defects in early stages, gives scope for action and is therefore a key element to avoid damage increase and to optimize the efficiency of wind turbines. One promising approach for damage detection is acoustic emission methods. Although most acoustic emission approaches use ultrasonic sound waves of the structure that require about 12 to 40 sensors to monitor one rotor blade, we propose to use the airborne sound in lower frequencies from about 500 Hz to 35 Hz with three optical microphones and present a signal model-based damage detection algorithm. The real-time algorithm uses six audio features from a spectrogram representation to detect damages and to estimate its significance. In a fatigue test of a 34-m blade, the algorithm detected the damage event and damage increasing without false detection. It was also tested with recordings inside an operating blade of a 3.4-MW wind turbine. In the recorded time period of about 1 year, the algorithm indicated no false detection.
AB - When operating a wind turbine, damage of rotor blades is a serious problem. Undetected damages are likely to increase overtime, and therefore, the safety risks and economical burdens also increase. A monitoring system, which detects reliably defects in early stages, gives scope for action and is therefore a key element to avoid damage increase and to optimize the efficiency of wind turbines. One promising approach for damage detection is acoustic emission methods. Although most acoustic emission approaches use ultrasonic sound waves of the structure that require about 12 to 40 sensors to monitor one rotor blade, we propose to use the airborne sound in lower frequencies from about 500 Hz to 35 Hz with three optical microphones and present a signal model-based damage detection algorithm. The real-time algorithm uses six audio features from a spectrogram representation to detect damages and to estimate its significance. In a fatigue test of a 34-m blade, the algorithm detected the damage event and damage increasing without false detection. It was also tested with recordings inside an operating blade of a 3.4-MW wind turbine. In the recorded time period of about 1 year, the algorithm indicated no false detection.
KW - acoustic emission
KW - acoustic signal processing
KW - airborne sound
KW - damage detection
KW - rotor blades
KW - wind energy
UR - http://www.scopus.com/inward/record.url?scp=85078936114&partnerID=8YFLogxK
U2 - 10.1002/stc.2520
DO - 10.1002/stc.2520
M3 - Article
AN - SCOPUS:85078936114
VL - 27
JO - Structural Control and Health Monitoring
JF - Structural Control and Health Monitoring
SN - 1545-2255
IS - 5
M1 - e2520
ER -