| 基于径向基函数神经网络的风力机结构适应性评估 |
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| 引用本文： | 王培德,刘朝丰,唐静,宋小飞. 基于径向基函数神经网络的风力机结构适应性评估[J]. 太阳能学报, 2021, 0(2): 185-188 |
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| 作者姓名： | 王培德 刘朝丰 唐静 宋小飞 |
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| 作者单位： | 北京金风科创风电设备有限公司 |
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| 摘 要： | 提出一种基于径向基函数神经网络(radial basis function,RBF)的风力机结构适应性评估方法,综合考虑多个载荷分量对风力机结构应力响应的影响.该新型适应性评估方法与当前采用的单变量、线性插值预测方法相比精度更高更可靠,与有限元方法相比更高效.采用该评估方法,1 min内可完成风力机机头部件及关键连接螺...
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| 关 键 词： | 风力发电机组 神经网络 应力 有限元分析 适应性评估 |
FLEXIBILITY EVALUATION OF WIND TURBINE STRUCTURE USING RADIAL BASIS FUNCTION NEURAL NETWORK |
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| Wang Peide,Liu Chaofeng,Tang Jing,Song Xiaofei. FLEXIBILITY EVALUATION OF WIND TURBINE STRUCTURE USING RADIAL BASIS FUNCTION NEURAL NETWORK[J]. Acta Energiae Solaris Sinica, 2021, 0(2): 185-188 |
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| Authors: | Wang Peide Liu Chaofeng Tang Jing Song Xiaofei |
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| Affiliation: | (Beijing Goldwind Science&Creation Wind Power Equipment Co.,Ltd.,Beijing 10017,China) |
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| Abstract: | A new wind turbine structure flexibility evaluation method based on the radial basis function(RBF)neural network is presented in this paper.The effect of multiple load components on the stracture stress of the wind turbine is comprehensively considered to wind stress into account.Compared with the current single variable and linear interpolation prediction methods,this new flexibility evaluation method has higher precision and is more reliable.Compared with the finite element method,it is no doubt a more efficient way.The strength evaluation of wind head parts and key connection bolt can be completed in one minute by using this evaluation method,and the maximum stress prediction error is less than 1%. |
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| Keywords: | wind turbine generator neural network stress finite element analysis flexibility evaluation |
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