Estimation of Wind Turbine Gearbox Loads for Online Fatigue Monitoring Using Inverse Methods
In this article a novel approach for the estimation of wind turbine gearbox loads with the purpose of online fatigue damage monitoring is presented. The proposed method employs a Digital Twin framework and aims at continuous estimation of the dynamic states based on CMS vibration data and generator...
| Published in: | Volume 9: Ocean Renewable Energy |
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| Main Authors: | , , |
| Format: | Book Part |
| Language: | English |
| Published: |
ASME
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/11250/3003424 https://doi.org/10.1115/OMAE2021-62181 |
| Summary: | In this article a novel approach for the estimation of wind turbine gearbox loads with the purpose of online fatigue damage monitoring is presented. The proposed method employs a Digital Twin framework and aims at continuous estimation of the dynamic states based on CMS vibration data and generator torque measurements from SCADA data. With knowledge of the dynamic states local loads at gearbox bearings are easily determined and fatigue models are be applied to track the accumulation of fatigue damage. A case study using simulation measurements from a high-fidelity gearbox model is conducted to evaluate the proposed method. Estimated loads at the considered IMS and HSS bearings show moderate to high correlation (R = 0.50–0.96) to measurements, as lower frequency internal dynamics are not fully captured. The estimated fatigue damage differs by 5–15 % from measurements. publishedVersion |
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