风力机叶片截面雨蚀损伤的机器学习辅助预测

A. Castorrini, P. Venturini, Fabrizio Gerboni, A. Corsini, F. Rispoli
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引用次数: 0

摘要

风力涡轮机叶片的雨水侵蚀是一个有趣的研究课题,因为它对安装在多雨地区的风力发电场的年发电量有着不可忽视的影响。最近有相当多的研究工作都是针对这一主题,提出了雨水侵蚀模型、性能损失预测、结构问题研究等。本工作旨在提出一种预测风力发电机叶片损伤的新方法。本文采用该方法研究了不同降雨条件和叶片涂层材料对正常湍流风条件下5MW参考涡轮叶片典型断面雨损的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning Aided Prediction of Rain Erosion Damage on Wind Turbine Blade Sections
Rain erosion of wind turbine blades represents an interesting topic of study due to its non-negligible impact on annual energy production of the wind farms installed in rainy sites. A considerable amount of recent research works has been oriented to this subject, proposing rain erosion modelling, performance losses prediction, structural issues studies, etc. This work aims to present a new method to predict the damage on a wind turbine blade. The method is applied here to study the effect of different rain conditions and blade coating materials, on the damage produced by the rain over a representative section of a reference 5MW turbine blade operating in normal turbulence wind conditions.
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