铺层材料单层厚度对风力机叶片低阶模态频率的影响分析

郑玉巧, 马辉东, 卢秉喜

太阳能学报 ›› 2022, Vol. 43 ›› Issue (9) : 337-342.

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (9) : 337-342. DOI: 10.19912/j.0254-0096.tynxb.2021-0271

铺层材料单层厚度对风力机叶片低阶模态频率的影响分析

  • 郑玉巧, 马辉东, 卢秉喜
作者信息 +

ANALYSIS OF EFFECT OF LAYUP MATERIAL LAYER THICKNESS ON LOW-ORDER MODEL FREQUENCY OF WIND TURBINE BLADES

  • Zheng Yuqiao, Ma Huidong, Lu Bingxi
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摘要

针对大型风力机叶片铺层材料单层厚度对叶片模态频率的影响作用,对铺层材料单层厚度间的耦合机制进行研究。采用Box-Behnken法设计实验,建立叶片铺层单层厚度与其第一阶模态频率间的响应面模型,揭示叶片不同铺层材料单层厚度对模态频率的影响规律。以叶片前两阶模态频率为优化目标、以铺层材料单层厚度为设计变量建立优化数学模型,并采用遗传算法与有限元法结合进行全局寻优。以某企业1.5 MW叶片为算例,结果表明,优化后叶片第一阶挥舞、摆振频率均提高了0.07 Hz。

Abstract

The effect of single-layer thickness of layup material on the modal frequency of large wind turbine blades is studied to investigate the coupling mechanism of single-layer thickness of layup material. By using the Box-Behnken method to design experiments, the response surface model between the single-layer thickness of the blade ply material and the first-order modal frequency is established to reveal the influence of the single-layer thickness of different ply materials on the modal frequency of the blade. Further, an optimization mathematical model with the first two orders of the blade modal frequency as the optimal target and the single-layer thickness of the layup material as the design variable is proposed, which uses a combination of genetic algorithm and finite element method for global optimization. The results show that the first-order falpwise and edgewise frequencies of the blade are increased by 0.07 Hz after optimization.

关键词

风力机 / 叶片 / 灵敏度分析 / 模态分析 / 单层厚度 / 响应面模型

Key words

wind turbines / blades / sensitivity analysis / modal analysis / single thickness / response surface model

引用本文

导出引用
郑玉巧, 马辉东, 卢秉喜. 铺层材料单层厚度对风力机叶片低阶模态频率的影响分析[J]. 太阳能学报. 2022, 43(9): 337-342 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0271
Zheng Yuqiao, Ma Huidong, Lu Bingxi. ANALYSIS OF EFFECT OF LAYUP MATERIAL LAYER THICKNESS ON LOW-ORDER MODEL FREQUENCY OF WIND TURBINE BLADES[J]. Acta Energiae Solaris Sinica. 2022, 43(9): 337-342 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0271
中图分类号: TK83   

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基金

国家自然科学基金(51965034); 兰州市人才创新创业项目(2018-RC-25)

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