TWO-STAGE RELIABILITY ASSESSMENT OF WIND TURBINE BLADES CONSIDERING RANDOM FAILURE THRESHOLDS

Liu Fei; Bi Junxi; Li Haibin; Ren Jun; Yang Shaonan; Qi Xiao

doi:10.19912/j.0254-0096.tynxb.2023-1295

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (12) : 269-276. DOI: 10.19912/j.0254-0096.tynxb.2023-1295

TWO-STAGE RELIABILITY ASSESSMENT OF WIND TURBINE BLADES CONSIDERING RANDOM FAILURE THRESHOLDS

Liu Fei¹, Bi Junxi¹, Li Haibin², Ren Jun³, Yang Shaonan⁴, Qi Xiao¹

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Abstract

To address the limitations of existing two-stage degradation reliability assessment methods for wind turbine blades, specifically the neglect of failure threshold randomness and the accuracy of changepoint detection in the degradation process, a novel approach is proposed. This method is based on a nonlinear Wiener degradation process and considers the impact of random failure thresholds across different stages. The corrected akaike information criterion （AICc） is introduced to determine the optimal changepoint location, followed by interval estimation. Maximum likelihood estimation is employed to determine the drift and diffusion coefficients for the two stages based on the identified changepoint. Subsequently, a reliability model for blade degradation is established using data obtained from fatigue crack propagation simulation experiments. To validate the accuracy of the model predictions, an empirical analysis is conducted using updated wind turbine blade data via an adaptive algorithm. The results demonstrate that accounting for failure threshold randomness and changepoint accuracy significantly impacts degradation modeling, thereby enhancing the precision of reliability assessments.

Key words

wind turbine blades / degradation / failure / maximum likelihood estimation / fatigue crack propagation / adaptive algorithms / reliability

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Liu Fei, Bi Junxi, Li Haibin, Ren Jun, Yang Shaonan, Qi Xiao. TWO-STAGE RELIABILITY ASSESSMENT OF WIND TURBINE BLADES CONSIDERING RANDOM FAILURE THRESHOLDS[J]. Acta Energiae Solaris Sinica. 2024, 45(12): 269-276 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1295

References

[1] 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.
[2] 胡姚刚, 刘怀盛, 时萍萍, 等. 风电机组偏航系统故障诊断与寿命预测综述[J]. 中国电机工程学报, 2022, 42(13): 4871-4884.
HU Y G, LIU H S, SHI P P, et al.Overview of fault diagnosis and life prediction for wind turbine yaw system[J]. Proceedings of the CSEE, 2022, 42(13): 4871-4884.
[3] 王国锋, 曹增欢, 冯海生, 等. 基于多阶段退化建模的谐波减速器实时可靠性评估与寿命预测[J]. 天津大学学报(自然科学与工程技术版), 2022, 55(2): 122-132.
WANG G F, CAO Z H, FENG H S, et al.Real-time reliability evaluation and life prediction of harmonic reducer based on multistage degradation modeling[J]. Journal of Tianjin University (science and technology), 2022, 55(2): 122-132.
[4] GADDAFEE M, CHINCHANIKAR S.An experimental investigation of cutting tool reliability and its prediction using weibull and gamma models: a comparative assessment[J]. Materials today: proceedings, 2020, 24: 1478-1487.
[5] 王小林, 郭波, 程志君. 基于分阶段Wiener-Einstein过程设备的实时可靠性评估[J]. 中南大学学报(自然科学版), 2012, 43(2): 534-540.
WANG X L, GUO B, CHENG Z J.Real-time reliability evaluation of equipment based on separated-phase Wiener-Einstein process[J]. Journal of Central South University (science and technology), 2012, 43(2): 534-540.
[6] 陈伟, 雷欢, 裴婷婷, 等. 基于退化轨迹和Wiener模型的光伏组件剩余寿命预测方法[J]. 太阳能学报, 2023, 44(7): 175-181.
CHEN W, LEI H, PEI T T, et al.Remaining life prediction method of photovoltaic modules based on degradation trajectoryand Wiener model[J]. Acta energiae solaris sinica, 2023, 44(7): 175-181.
[7] 王延忠, 鄂世元, 谢斌. 基于非齐次Gamma过程的滚动轴承磨损随机过程建模方法[J]. 新技术新工艺, 2023(4): 74-76.
WANG Y Z, E S Y, XIE B. Modeling method of rolling bearing wear stochastic process based on inhomogeneous Gamma process[J]. New technology & new process, 2023(4): 74-76.
[8] 马强, 安宗文, 寇海霞. 考虑随机失效阈值的退化数据建模分析方法[J]. 兰州理工大学学报, 2017, 43(5): 40-46.
MA Q, AN Z W, KOU H X.Degraded data modeling and analysis method taking account of random failure threshold[J]. Journal of Lanzhou University of Technology, 2017, 43(5): 40-46.
[9] 王玺, 胡昌华, 任子强, 等. 基于非线性Wiener过程的航空发动机性能衰减建模与剩余寿命预测[J]. 航空学报, 2020, 41(2): 195-205.
WANG X, HU C H, REN Z Q, et al.Performance degradation modeling and remaining useful life prediction for aero-engine based on nonlinear Wiener process[J]. Acta aeronautica et astronautica sinica, 2020, 41(2): 195-205.
[10] 鄢伟安, 宋保维, 段桂林, 等. 基于两阶段维纳退化过程的液力耦合器可靠性评估[J]. 系统工程与电子技术, 2014, 36(9): 1882-1886.
YAN W A, SONG B W, DUAN G L, et al.Reliability evaluation of LCD based on two-phase Wiener degradation process[J]. Systems engineering and electronics, 2014, 36(9): 1882-1886.
[11] 姜洋. 基于两阶段Gamma过程的机械产品剩余寿命预测研究[J]. 机电工程, 2021, 38(6): 802-806.
JIANG Y.Remaining useful lifetime prediction of the mechanical products based on the two-phase Gamma process[J]. Journal of mechanical & electrical engineering, 2021, 38(6): 802-806.
[12] 张奡, 王治华, 赵振平, 等. 两阶段非线性Wiener过程退化建模与可靠性分析[J]. 系统工程与电子技术, 2020, 42(4): 954-959.
ZHANG A, WANG Z H, ZHAO Z P, et al.Two-phase nonlinear Wiener process for degradation modeling and reliability analysis[J]. Systems engineering and electronics, 2020, 42(4): 954-959.
[13] 高新, 叶楠, 周坤, 等. 考虑测量误差的两阶段Wiener建模与可靠性分析[J]. 中国机械工程, 2023, 34(9): 1067-1076.
GAO X, YE N, ZHOU K, et al.Two stage Wiener modeling and reliability analysis considering measurement errors[J]. China mechanical engineering, 2023, 34(9): 1067-1076.
[14] WEI M H, CHEN M Y, ZHOU D H.Multi-sensor information based remaining useful life prediction with anticipated performance[J]. IEEE transactions on reliability, 2013, 62(1): 183-198.
[15] WANG J H, ZHANG L A, HUANG X M, et al.Initiation mechanism of transverse cracks in wind turbine blade trailing edge[J]. Energy engineering, 2022, 119(1): 407-418.
[16] WEN Y X, WU J G, DAS D, et al.Degradation modeling and RUL prediction using Wiener process subject to multiple change points and unit heterogeneity[J]. Reliability engineering & system safety, 2018, 176: 113-124.