As hybrid towers of wind turbines have gradually become the mainstream structural configuration for high-power wind turbines, their structural safety and long-term reliability have increasingly become critical issues. However, existing studies have insufficiently focused on the impacts of environmental factors and local structural characteristics on hybrid tower structures. To address this gap, this study investigates the dynamic characteristics of wind turbine hybrid towers based on Operational Modal Analysis (OMA) and finite element simulation. This study proposes a systematic operational modal analysis process. Compared with traditional modal identification methods, the proposed approach combines the Frequency Domain Decomposition (FDD) method and the Stochastic Subspace Identification–Covariance (SSI-COV) method to achieve effective extraction of structural modal frequencies and mode shapes under operational conditions. Through a progressive strategy involving preliminary identification, accurate estimation, and spurious mode elimination, the efficiency and accuracy of modal parameter identification are significantly improved. The analysis results show that, within the range of conventional environmental variations, no significant statistical correlation is observed between the identified modal parameters (frequency and mode shape) and environmental factors, including wind direction, wind speed, and temperature. It should be noted that the validity of these conclusions is limited to the specific environmental conditions and data acquisition periods investigated in this study—namely, wind speeds of 2.0–5.5 m/s, temperatures of 17 °C–35.8 °C, wind direction variations of approximately 10°, and data collected daily between 11:45 and 12:15—and does not encompass seasonal-scale extreme environmental variations. Meanwhile, a finite element model of the wind turbine hybrid tower is established and its effectiveness is verified using on-site measured data. Parametric analysis and damage simulation based on the validated model reveal that the elastic modulus of concrete is the most sensitive parameter affecting the overall dynamic characteristics of the structure, compared with the elastic moduli of steel and the foundation. Additionally, the influence of stiffness degradation in different regions of the concrete tower on the natural frequencies of each order is related to the specific location of damage and the modal order of structural vibration. The conclusions of this study provide a theoretical basis for the optimal design of wind turbine hybrid tower structures and offer important references for formulating structural health monitoring strategies based on dynamic characteristics.

Research on dynamic characteristics of wind turbine hybrid towers under environmental influences based on operational modal identification and refined finite element simulation / Xing, Kankan; Zhang, Zhenli; Tang, Shengbo; Jiang, Weitao; Lacidogna, Giuseppe; Xu, Jie. - In: FRONTIERS IN BUILT ENVIRONMENT. - ISSN 2297-3362. - STAMPA. - 11:(2026), pp. 1-21. [10.3389/fbuil.2025.1728006]

Research on dynamic characteristics of wind turbine hybrid towers under environmental influences based on operational modal identification and refined finite element simulation

Lacidogna, Giuseppe;
2026

Abstract

As hybrid towers of wind turbines have gradually become the mainstream structural configuration for high-power wind turbines, their structural safety and long-term reliability have increasingly become critical issues. However, existing studies have insufficiently focused on the impacts of environmental factors and local structural characteristics on hybrid tower structures. To address this gap, this study investigates the dynamic characteristics of wind turbine hybrid towers based on Operational Modal Analysis (OMA) and finite element simulation. This study proposes a systematic operational modal analysis process. Compared with traditional modal identification methods, the proposed approach combines the Frequency Domain Decomposition (FDD) method and the Stochastic Subspace Identification–Covariance (SSI-COV) method to achieve effective extraction of structural modal frequencies and mode shapes under operational conditions. Through a progressive strategy involving preliminary identification, accurate estimation, and spurious mode elimination, the efficiency and accuracy of modal parameter identification are significantly improved. The analysis results show that, within the range of conventional environmental variations, no significant statistical correlation is observed between the identified modal parameters (frequency and mode shape) and environmental factors, including wind direction, wind speed, and temperature. It should be noted that the validity of these conclusions is limited to the specific environmental conditions and data acquisition periods investigated in this study—namely, wind speeds of 2.0–5.5 m/s, temperatures of 17 °C–35.8 °C, wind direction variations of approximately 10°, and data collected daily between 11:45 and 12:15—and does not encompass seasonal-scale extreme environmental variations. Meanwhile, a finite element model of the wind turbine hybrid tower is established and its effectiveness is verified using on-site measured data. Parametric analysis and damage simulation based on the validated model reveal that the elastic modulus of concrete is the most sensitive parameter affecting the overall dynamic characteristics of the structure, compared with the elastic moduli of steel and the foundation. Additionally, the influence of stiffness degradation in different regions of the concrete tower on the natural frequencies of each order is related to the specific location of damage and the modal order of structural vibration. The conclusions of this study provide a theoretical basis for the optimal design of wind turbine hybrid tower structures and offer important references for formulating structural health monitoring strategies based on dynamic characteristics.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3006916