基于全局模态特性的海上风力机导管套结构损伤检测与定位方法

D. Cevasco, J. Tautz-Weinert, M. Richmond, A. Sobey, A. Kolios
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引用次数: 1

摘要

海上风力发电机组子结构的结构失效可能比风力发电机组其他设备的故障发生的可能性小,但由于可能造成灾难性后果,因此具有很高的风险。检查和维护等海上作业的成本很高,因此远程监控有望实现经济高效的结构完整性管理。这项工作的目的是研究两级检测的可行性,在异常识别和定位方面,在海上风力发电机的导管套结构。基于结构模态特性数据库,提出了一种针对不同情况的监测方案。该方法基于固有频率、模态振型间模态保证准则和模态柔度变化三种模态指标识别出正确的异常情景。应用监督Fisher线性判别分析对模态指标进行变换,使异常情景的可分性最大化。训练模糊聚类算法来预测新数据与数据库中场景的隶属关系。在一个案例研究中,模拟了极端冲刷现象和夹套构件完整性损失,以及环境和操作条件下结构动力学的变化。交叉验证用于选择最佳超参数,并通过环境条件的微小变化验证聚类的有效性。结果表明,通过对海上风导管架结构的全局监测,对模拟情景进行检测和定位是可行的。
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A Damage Detection and Location Scheme for Offshore Wind Turbine Jacket Structures Based On Global Modal Properties
Structural failures of offshore wind turbine substructures might be less likely than failures of other equipment of the wind turbine generator but pose a high risk due to the possibility of catastrophic consequences. Significant costs are linked to offshore operations like inspections and maintenance, thus remote monitoring shows promise for cost-efficient structural integrity management. This work is aimed to investigate the feasibility of the two-level detection, in terms of anomaly identification and localisation, in the jacket structure of an offshore wind turbine. A monitoring scheme is developed based on a database of modal properties of the structure for different scenarios. The method identifies the correct anomaly scenario based on three types of modal indicators, namely natural frequency, the modal assurance criterion between mode shapes, and the modal flexibility variation. The supervised Fisher's linear discriminant analysis is applied to transform the modal indicators to maximise the separability of anomaly scenarios. A Fuzzy clustering algorithm is trained to predict the membership of new data to the scenarios in the database. In a case study, extreme scour phenomena and jacket member integrity loss are simulated, together with variations of the structural dynamics for environmental and operating conditions. Cross-validation is used to select the best hyperparameters and the effectiveness of the clustering is validated with slight variations of the environmental conditions. The results prove that it is feasible to detect and localise the simulated scenarios via the global monitoring of an offshore wind jacket structure.
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来源期刊
CiteScore
5.20
自引率
13.60%
发文量
34
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