该文讨论了叶片延寿相关的标准体系及要求,依据延寿评估程序,提出疲劳累积损伤条件下的叶片延寿评估方法。首先,在役工况下测量挥舞和摆振方向叶片根部弯矩载荷,并获取叶片所经历的风速和湍流强度,建立俘获矩阵。其次,结合雨流计数法、等效载荷变换和Miner准则进行累积损伤计算,以瑞利分布构建疲劳载荷谱。接着,以累积损伤和已工作寿命年限,计算年度损伤值,求出累积总损伤不超过疲劳破坏临界损伤值的延寿区间。最后,以某型1.5 MW叶片为例进行延寿评估,验证方法的可行性。
Abstract
Focusing on the standard system and running requirements related to the wind turbine blades, a method for life extension assessment of wind turbine blades is proposed under cumulative damage conditions. Firstly, measurements are taken of the bending moment loads at the blade root in both the flap-wise and edge-wise directions in-service conditions. Then the wind speed and turbulence intensity experienced by the blade are obtained to establish a capture matrix. Subsequently, the cumulative damage calculation is performed by combining the rainfall counting method, equivalent load transformation and the Miner criterion. The Rayleigh distribution is employed to build the fatigue load spectrum. Next, the annual damage value is calculated based on the cumulative damage and the years of service life. The determination of the life extension span is based on the premise that the cumulative total damage does not surpass the critical damage threshold for fatigue failure. Finally, the life extension assessment is carried out with a 1.5 MW blade as an example to verify the feasibility of the method.
关键词
风电叶片 /
累积损伤 /
弯矩载荷 /
风速 /
延寿
Key words
wind turbine blades /
cumulative damage /
bending moment load /
wind speed /
life extension
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参考文献
[1] LI H, XIN W, XU B F, et al.Delamination failure analysis of wind turbine blades based on equivalent fatigue load[J]. Ocean engineering, 2024, 310: 118642.
[2] SPINI F, BETTINI P.End-of-Life wind turbine blades: review on recycling strategies[J]. Composites part B: engineering, 2024, 275: 111290.
[3] GB/T 18451.1-2022, 风力发电机组设计要求[S].
GB/T 18451.1-2022, Wind energy generation systems: design requirements[S].
[4] IEC 61400-1:2019, Wind energy generation systems-Part1: Design requirements[S].
[5] IEC 61400-28:2025, Wind energy generation systems - part 28: through-life management and life extension of wind power assets[S].
[6] UL4143-2018, Wind turbine generator-life time extension[S].
[7] DNVGL-SE-0262, Lifetime extension of wind turbines[S].
[8] DNVGL-SE-0263, Certification of lifetime extension of wind turbines[S].
[9] CGC/GF 149, 风力发电机组延寿技术规范[S].
CGC/GF 149, Technical specifications for extending the lifespan of wind turbines[S].
[10] 葛新宇, 毕俊喜, 李海滨, 等. 基于故障物理的风力机叶片可靠性仿真分析方法[J]. 太阳能学报, 2024, 45(3): 29-40.
GE X Y, BI J X, LI H B, et al.Reliability simulation analysis method of wind turbine blades based on fault physics[J]. Acta energiae solaris sinica, 2024, 45(3): 29-40.
[11] 马航, 毕俊喜, 葛新宇, 等. 基于优化等寿命疲劳极限模型的风力机叶片寿命预测[J]. 太阳能学报, 2023, 44(10): 362-369.
MA H, BI J X, GE X Y, et al.Service life prediction of wind turbine blade based on optimizated constant life fatigue limit model[J]. Acta energiae solaris sinica, 2023, 44(10): 362-369.
[12] 赵琴. 考虑风速风向联合概率分布的风力机叶片疲劳寿命研究[D]. 乌鲁木齐: 新疆大学, 2021.
ZHAO Q.Study on fatigue life of wind turbine blades considering joint probability distribution of wind speed and direction[D]. Urumqi: Xinjiang University, 2021.
[13] ZHANG C Z, CHEN H P, TEE K F, et al.Reliability-based lifetime fatigue damage assessment of offshore composite wind turbine blades[J]. Journal of aerospace engineering, 2021, 34(3): 04021019.
[14] RUBIELLA C, HESSABI C A, FALLAH A S.State of the art in fatigue modelling of composite wind turbine blades[J]. International journal of fatigue, 2018, 117: 230-245.
[15] SANCHEZ H, SANKARARAMAN S, ESCOBET T, et al.Analysis of two modeling approaches for fatigue estimation and remaining useful life predictions of wind turbine blades[C]//PHM Society European conference, 2016, 3(1): 1-11.
[16] NIELSEN J S, MILLER-BRANOVACKI L, CARRIVEAU R.Probabilistic and risk-informed life extension assessment of wind turbine structural components[J]. Energies, 2021, 14(4): 821.
[17] GB/T 37257—2018, 风力发电机组机械载荷测量[S].
GB/T 37257—2018, Wind turbines-measurement of mechanical loads[S].
基金
国家自然科学基金（52365017）; 市场监督管理总局科技计划（2022MK125）; 甘肃省科技计划（22YF7GA072）; 兰州市青年科技人才创新项目（2023-QN-35）
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