TY - JOUR

T1 - In-situ monitoring of an offshore wind turbine blade using acceleration and strain measurements

AU - Bonilla, David

AU - Jonscher, Clemens

AU - Wolniak, Marlene

AU - Jauken, Helge

AU - Liesecke, Leon

AU - Grießmann, Tanja

AU - Rolfes, Raimund

N1 - Publisher Copyright: © 2024 11th European Workshop on Structural Health Monitoring, EWSHM 2024. All rights reserved.

PY - 2024/7/1

Y1 - 2024/7/1

N2 - One of the most critical components of wind turbines is the blades. As blades are constantly exposed to weather and high loads, they can wear and become damaged. Performing in-situ continuous monitoring can help detect sudden damages and prevent further degradation, which is imperative to avoid economic losses and fatal accidents. However, monitoring a rotating rotor blade presents some challenges. One challenge is the consideration of lightning protection. Hence, a non-conductor measurement system must be used. Another challenge is system identification and modal tracking considering environmental and operational conditions (EOCs). Furthermore, vibration-based monitoring results from actual and operational rotor blades are scarce in the existing literature. This study centres on operational modal analysis (OMA) using covariance-driven stochastic subspace identification (SSI-COV) of an offshore wind turbine blade in operation employing eight months of data from fibre optic accelerometers (FOA) and fibre Bragg grating (FBG) strain gauges. The identification focuses on the first two bending modes in flapwise and edgewise directions and the first torsional mode. The study aims to determine which fibre optic sensor delivers better results. Furthermore, it addresses the effect of EOCs on the modal parameters, where system identification and modal tracking are discussed. It was found that tracked modes showed similar trends with respect to time, and a high connection was observed between wind speed, rotor speed, and pitch angle with frequency and damping. Additionally, acceleration and strain measurements deliver the same frequency and damping values. FBG better identified the first flapwise mode. On the other hand, FOA was superior in almost all other modes. This study points towards employing FOA for vibration-based monitoring of wind turbine blades using modal parameters.

AB - One of the most critical components of wind turbines is the blades. As blades are constantly exposed to weather and high loads, they can wear and become damaged. Performing in-situ continuous monitoring can help detect sudden damages and prevent further degradation, which is imperative to avoid economic losses and fatal accidents. However, monitoring a rotating rotor blade presents some challenges. One challenge is the consideration of lightning protection. Hence, a non-conductor measurement system must be used. Another challenge is system identification and modal tracking considering environmental and operational conditions (EOCs). Furthermore, vibration-based monitoring results from actual and operational rotor blades are scarce in the existing literature. This study centres on operational modal analysis (OMA) using covariance-driven stochastic subspace identification (SSI-COV) of an offshore wind turbine blade in operation employing eight months of data from fibre optic accelerometers (FOA) and fibre Bragg grating (FBG) strain gauges. The identification focuses on the first two bending modes in flapwise and edgewise directions and the first torsional mode. The study aims to determine which fibre optic sensor delivers better results. Furthermore, it addresses the effect of EOCs on the modal parameters, where system identification and modal tracking are discussed. It was found that tracked modes showed similar trends with respect to time, and a high connection was observed between wind speed, rotor speed, and pitch angle with frequency and damping. Additionally, acceleration and strain measurements deliver the same frequency and damping values. FBG better identified the first flapwise mode. On the other hand, FOA was superior in almost all other modes. This study points towards employing FOA for vibration-based monitoring of wind turbine blades using modal parameters.

KW - fibre optic sensors

KW - In-situ monitoring

KW - offshore wind turbine

KW - operational modal analysis

KW - rotor blade

UR - http://www.scopus.com/inward/record.url?scp=85202639979&partnerID=8YFLogxK

U2 - 10.58286/29634

DO - 10.58286/29634

M3 - Article

VL - 29

JO - e-Journal of Nondestructive Testing

JF - e-Journal of Nondestructive Testing

SN - 1435-4934

IS - 7

ER -