| 兆瓦级风力机结构系统可靠性分析的样本分数阶矩最大熵方法 |
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| 引用本文： | 黄德胜,张旭方,S,rensen John Dalsgaard. 兆瓦级风力机结构系统可靠性分析的样本分数阶矩最大熵方法[J]. 太阳能学报, 2022, 43(7): 293-301. DOI: 10.19912/j.0254-0096.tynxb.2020-1241 |
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| 作者姓名： | 黄德胜 张旭方 S rensen John Dalsgaard |
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| 作者单位： | 1.东北大学机械工程与自动化学院,沈阳 110819; 2.丹麦奥尔堡大学土木工程学院,奥尔堡 DK-9220 |
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| 基金项目： | 国家自然科学基金（51775095）； |
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| 摘 要： | 以兆瓦级风力机塔架和叶片极限载荷的概率外推模型为基础,结合载荷动态响应峰值的独立同分布假设和三参数威布尔模型,外推获取了正常湍流和极端湍流强度条件下风力机关键部件长期服役载荷概率分布;进一步通过无量纲极值统计量定义系统失效的结构可靠性状态函数,结合样本分数阶矩和最大熵理论提出兆瓦级风力机关键部件结构可靠性分析的数值方法,对比湍流模型对兆瓦级风力机关键部件结构失效概率的影响。计算结果表明：样本分数阶矩最大熵方法能有效重构结构可靠性状态函数的概率分布;基于无量纲极值统计量的系统可靠性建模方法能有效表征风力机关键部件耦合相关失效问题,结合该文方法可获得系统失效概率的准确预测结果;湍流模型对风力机结构失效概率影响较大,难以预先判定何种模型将得到结构失效概率的保守预估结果,需结合IEC 61400-1标准中的设计载荷工况细致分析后才能确定。
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| 关 键 词： | 风力机 最大熵方法 概率分布 湍流模型 可靠性分析 |
| 收稿时间： | 2020-11-17 |
SYSTEM RELIABILITY ANALYSIS OF MEGAWATT WIND TURBINE STRUCTURES WITH PRINCIPLE OF MAXIMUM ENTROPY AND SAMPLE-BASED FRACTIONAL MOMENTS |
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| Huang Desheng,Zhang Xufang,S,#xf,rensen John Dalsgaard. SYSTEM RELIABILITY ANALYSIS OF MEGAWATT WIND TURBINE STRUCTURES WITH PRINCIPLE OF MAXIMUM ENTROPY AND SAMPLE-BASED FRACTIONAL MOMENTS[J]. Acta Energiae Solaris Sinica, 2022, 43(7): 293-301. DOI: 10.19912/j.0254-0096.tynxb.2020-1241 |
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| Authors: | Huang Desheng Zhang Xufang S rensen John Dalsgaard |
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| Affiliation: | 1. School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China; 2. Department of Civil Engineering, Aalborg University, Aalborg DK-9220, Denmark |
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| Abstract: | This paper presents an effective approach for system reliability analysis of megawatt wind turbine structures with the principle of maximum entropy and sample-based fractional moments. To begin with, a probabilistic model for the long-term extreme-valued structural loads （e.g. the annual, the twenty- or fifty-year return period） is derived based on the order statistic theory and the three-parameter Weibull distribution. This is further used to define performance functions for the reliability analysis of wind blade and tower structures. With fractional moments estimated based on a small number of samples, probability distribution of the system performance function is recovered through the principle of maximum entropy （MaxEnt） with sample-based fractional moments （ME-SFM）. In numerical examples, the structural performance functions are defined by bending moments of the blade and tower, whereas the dimensionless statistics reference to material strength are derived to model the system failure events. Numerical examples have shown that the predicted structural failure probability results provided by the proposed ME-SFM approach are in closed agreement with that of the Monte-Carlo simulation. The normal and extreme turbulence models significantly influence the system failure probability level, whereas the effect needs to be carefully evaluated by various wind load cases in the IEC 61400-1 standard. |
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| Keywords: | wind turbines maximum entropy method probability distributions turbulence models reliability analysis |
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