考虑表面形貌的风电主轴疲劳强度分析研究

黄敬博, 龙凯, 程正坤, 张锦华, 张惠

太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 621-626.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (8) : 621-626. DOI: 10.19912/j.0254-0096.tynxb.2025-0505

考虑表面形貌的风电主轴疲劳强度分析研究

  • 黄敬博1, 龙凯1, 程正坤2, 张锦华3, 张惠1
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FATIGUE STRENGTH ANALYSIS OF WIND POWER SPINDLE CONSIDERING SURFACE TOPOGRAPHY

  • Huang Jingbo1, Long Kai1, Cheng Zhengkun2, Zhang Jinhua3, Zhang Hui1
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摘要

为考察表面形貌对疲劳强度的影响,提出采用谐波叠加方式重构表面形貌,推导应力集中系数和疲劳缺口系数的解析表达式,结合DNVGL认证规范修正其中的经验公式项。以某风电机组主轴为研究对象,分别基于传统DNVGL规范和提出方法计算得到其累积疲劳损伤分布。结果表明,在特定参数下,两种方法的结果具有一致性。在相同表明粗糙度Rz下,所提方法揭示了疲劳损伤值随表面形貌波长的增大而减小,该结果证明实测构件表面形貌对疲劳强度定量分析具有必要性。

Abstract

To investigate the influence of surface topography on fatigue strength, a harmonic superposition method was proposed for reconstructing surface topography, the analytical expressions of stress concentration coefficient and fatigue notch coefficient were derived, and the empirical formula terms were revised in accordance with DNVGL certification. Based on the DNVGL specification and the proposed method, the cumulative fatigue damage distribution of a wind turbine mainshaft was calculated. The results indicate that within certain conditions, the results of the two approaches are congruent. Under the identical Rz, the fatigue damage value decreases as the surface topography wavelength increases, hence proving the imperative for quantitative analysis of fatigue strength based on measured surface topography.

关键词

风电机组 / 疲劳强度 / 表面粗糙度 / 表面重构 / 应力集中 / 应力寿命曲线

Key words

wind turbines / fatigue strength / surface roughness / surface reconstruction / stress concentration / stress-life curve

引用本文

导出引用
黄敬博, 龙凯, 程正坤, 张锦华, 张惠. 考虑表面形貌的风电主轴疲劳强度分析研究[J]. 太阳能学报. 2026, 47(8): 621-626 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0505
Huang Jingbo, Long Kai, Cheng Zhengkun, Zhang Jinhua, Zhang Hui. FATIGUE STRENGTH ANALYSIS OF WIND POWER SPINDLE CONSIDERING SURFACE TOPOGRAPHY[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 621-626 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0505
中图分类号: TH12   

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基金

重点研发计划(2024YFE0208600); 深圳市科技计划(2023112809331200); 深圳职业技术大学基金(6024310039K); 国家自然科学基金(U24B2090)

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