Investigation on vibration behavior of onshore wind turbine tower based on long-term monitoring data

To study the structural characteristics of onshore wind turbines under a range of environmental and operational conditions, a 2.0 MW onshore wind turbine tower was monitored for a period of 3 years. Based on the long-term field monitoring data, a statistical analysis of the vibration of the wind turbine and environmental factors was conducted. Then, a method based on covariance analysis was applied to determine the modal parameters of the wind turbine tower. In addition, the operating conditions of the wind turbine were divided. The effects of different operating conditions on the first three orders of frequency and damping ratio of the wind turbine tower were thoroughly examined. Finally, Campbell diagrams for the wind turbine in the X and Y directions were generated. The results indicate that the wind turbine blade speed at the third frequency (0.35 Hz) was nearly identical to the tower's fundamental frequency, which could potentially lead to structural resonance. Additionally, the blade speed of 7 rpm in the wind turbine causes the jump phenomenon, which is consistent with the non-linear jump phenomenon observed in the Sommerfeld effect during the transition from pre-resonance to post-resonance. This phenomenon provides an explanation for the peak of the RMS (root mean square) of the tower at wind speeds of 3 and 8 m/s vibration amplitude, thereby confirming the existence of resonance in the wind turbine. Consequently, the long-term monitoring of the wind turbine provides a basis for the design and assessment of the condition of wind turbine towers.

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Publication Details

Journal
Journal of Renewable and Sustainable Energy
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0249064
Citations
2
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
1.91

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article

Investigation on vibration behavior of onshore wind turbine tower based on long-term monitoring data

Qingxin Zhu, Wenhai Zhao, Wanrun Li, Yongfeng Du et al.
2 citations
Journal of Renewable and Sustainable Energy
Structural Health Monitoring Techniques
1.91
article

Investigation on vibration behavior of onshore wind turbine tower based on long-term monitoring data

Qingxin Zhu, Wenhai Zhao, Wanrun Li, Yongfeng Du, 李加福 LI Jia-fu
article en
2 citations

Abstract

To study the structural characteristics of onshore wind turbines under a range of environmental and operational conditions, a 2.0 MW onshore wind turbine tower was monitored for a period of 3 years. Based on the long-term field monitoring data, a statistical analysis of the vibration of the wind turbine and environmental factors was conducted. Then, a method based on covariance analysis was applied to determine the modal parameters of the wind turbine tower. In addition, the operating conditions of the wind turbine were divided. The effects of different operating conditions on the first three orders of frequency and damping ratio of the wind turbine tower were thoroughly examined. Finally, Campbell diagrams for the wind turbine in the X and Y directions were generated. The results indicate that the wind turbine blade speed at the third frequency (0.35 Hz) was nearly identical to the tower's fundamental frequency, which could potentially lead to structural resonance. Additionally, the blade speed of 7 rpm in the wind turbine causes the jump phenomenon, which is consistent with the non-linear jump phenomenon observed in the Sommerfeld effect during the transition from pre-resonance to post-resonance. This phenomenon provides an explanation for the peak of the RMS (root mean square) of the tower at wind speeds of 3 and 8 m/s vibration amplitude, thereby confirming the existence of resonance in the wind turbine. Consequently, the long-term monitoring of the wind turbine provides a basis for the design and assessment of the condition of wind turbine towers.

Journal of Renewable and Sustainable EnergyVol. 17(2)
University of Shanghai for Science and Technology (CN), Lanzhou University of Technology (CN)
National Natural Science Foundation of China, Science Fund for Distinguished Young Scholars of Gansu Province
Openalex Percentile: Top 17%
Structural Health Monitoring Techniques
1.91
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