【摘 要】
：
通过神经网络建立数学模型,利用 Multibrid M5000风力机实测的运行信号对叶片拍打弯矩、叶片弦向弯矩、塔筒弯矩和塔筒转矩的等效载荷进行了评估。同时分析了不同运行参数对
【机 构】
：
西北工业大学旋转机械与风能装置测控研究所,德国斯图加特大学飞行器设计研究所,
论文部分内容阅读
通过神经网络建立数学模型,利用 Multibrid M5000风力机实测的运行信号对叶片拍打弯矩、叶片弦向弯矩、塔筒弯矩和塔筒转矩的等效载荷进行了评估。同时分析了不同运行参数对评估效果的影响程度。通过与实测结果比较表明,该方法可以在避免测试风力机载荷的情况下获得载荷的评估结果,具有较高的精度,可以用来预测风力机的寿命。
The mathematic model was established by neural network and the equivalent load of blade bending moment, blade chord bending moment, tower bending moment and towering torque was evaluated by the operating signals measured by Multibrid M5000 wind turbine. At the same time, the influence of different operating parameters on the evaluation results was analyzed. The comparison with the measured results shows that this method can get the result of the load assessment without the need to test the load of the wind turbine, and has a high accuracy and can be used to predict the life of the wind turbine.
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