导管架式海上风电结构模态参数识别研究

doi:doi:10.19912/j.0254-0096.tynxb.2024-0813

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导管架式海上风电结构模态参数识别研究

更新时间：2025-10-22

- 导管架式海上风电结构模态参数识别研究
- Vol. 46, Issue 9, Pages: 108-115(2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-0813
  CLC： TK8
- Published Online：14 October 2025，
  
  Published：2025
- 稿件说明：
移动端阅览
[J]. 2025, 46(9): 108-115.
DOI：

[J]. 2025, 46(9): 108-115. DOI： doi:10.19912/j.0254-0096.tynxb.2024-0813.

摘要

开展大型导管架式风电结构运行状态下的模态参数识别研究

并研究在非理想白噪声激励条件下识别结果的鲁棒性。结合层次聚类算法

建立协方差驱动随机子空间法（COV-SSI）

实现风电结构模态参数自动识别。首先基于平稳激励下的三层框架数值算例

验证提出的识别方法的有效性与准确性;再基于大型导管架式基础海上风电结构缩尺试验

研究风力机在不同风浪激励下运行的模态识别方法的识别精度

分析典型运行工况条件下COV-SSI方法的鲁棒性。结果表明

在额定风速下该方法可有效识别结构的前两阶固有频率和振型

精度较高。

Abstract

A study on modal parameter identification of large jacket offshore wind turbine structures under operating conditions was carried out

and the robustness of the method under non-ideal white noise excitation conditions was investigated. Combined with hierarchical clustering algorithm

the covariance-driven stochastic subspace identification（COV-SSI） method was established to realize the automatic identification of modal parameters of wind turbine structures. The effectiveness and accuracy of the proposed identification method were firstly verified based on a numerical example of a three-story frame under stationary excitation. Then

based on scaled experiments of offshore wind turbine structure with a large jacket foundation

the accuracy and robustness of the modal identification method for offshore wind turbine under different wind and wave excitations were investigated. The results show that under rated wind speed

the method can effectively identify the first two natural frequencies and modal shapes of the structure with high accuracy.

关键词

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