System identification and finite element model updating of a 6 MW offshore wind turbine using vibrational response measurements
System identification and finite element model updating of a 6 MW offshore wind turbine using vibrational response measurements
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DOI：
10.1016/j.renene.2023.119430
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发表时间：
2023-10
期刊：
影响因子：
8.7
通讯作者：
Bridget Moynihan;Azin Mehrjoo;B. Moaveni;Ross McAdam;F. Rüdinger;Eric Hines
中科院分区：
文献类型：
--
作者：
Bridget Moynihan;Azin Mehrjoo;B. Moaveni;Ross McAdam;F. Rüdinger;Eric Hines
海上风能在全球清洁能源转型中发挥着越来越重要的作用，而提高风力机结构的可靠性对于可再生能源的长期成功和效率是必不可少的。可靠性的提高将减少与故障相关的维护成本，进而降低海上风能能源的统一能源成本。结构健康监测方法可以通过持续监测仪器结构来预测破损和延长使用寿命。本文介绍了一台6兆瓦海上风力机在不同运行条件下的系统辨识和模型修正。涡轮机是单柱支撑的，并在塔和单柱的几个高度上安装了应变计和加速计。模型中土壤弹簧的有效刚度被更新，以使前两个振型的固有频率和振型与不同工况下的测量结果相匹配。比较了确定性和概率(贝叶斯)模型修正方法。研究了识别出的模态参数和更新后的模型参数对运行和环境条件(如风速)的敏感性。结果表明，确定性模型修正可以跨数据集和环境条件高精度地匹配模态参数。贝叶斯模型修正结果成功地估计了修正模型参数的后验分布，并且随着使用的数据越来越多，确定性越来越高。
Offshore wind energy is playing an increasingly vital role in the clean energy transition around the world, and improved reliability of wind turbine structures is necessary for the long-term success and efficiency of renewable energy. Increased reliability would reduce costs associated with maintenance due to breakages and in turn reduce the levelized cost of energy for offshore wind energy sources. Structural health monitoring methods can be used to predict breakages and extend lifetimes by continuously monitoring instrumented structures. This paper presents system identification and model updating of a 6 MW offshore wind turbine using vibration measurements under varying operational conditions. The turbine is monopile-supported and instrumented with strain gauges and accelerometers at several elevations along the tower and monopile. Effective stiffness of soil springs in the model are updated to match modal-predicted natural frequencies and mode shapes of the first two modes with those identified from measurements at different operating conditions. A deterministic and probabilistic (Bayesian) approach to model updating are compared. The sensitivity of identified modal parameters and the updated model parameters are investigated with respect to operational and environmental conditions such as wind speed. Results show that deterministic model updating can match modal parameters with high accuracy across datasets and environmental conditions. Bayesian model updating results successfully estimate the posterior distribution of updating model parameters with an increasing degree of certainty as more data is used.