REFERENCES
1. de Azevedo HDM, Araújo AM, Bouchonneau N. A review of wind turbine bearing condition monitoring: state of the art and challenges. Renew Sustain Energy Rev 2016;56:368-79.
3. Yang W, Tavner PJ, Crabtree CJ, Wilkinson M. Cost-effective condition monitoring for wind turbines. IEEE Trans Ind Electron 2010;57:263-71.
4. Mcmillan D, Ault GW. Condition monitoring benefit for onshore wind turbines: sensitivity to operational parameters. IET Renew Power Gen 2008;2:60-72.
5. Meng D, Yang H, Yang S, et al. Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy. Ocean Eng 2024;295:116842.
6. Meng D, Yang S, Yang H, De Jesus AMP, Correia J, Zhu SP. Intelligent-inspired framework for fatigue reliability evaluation of offshore wind turbine support structures under hybrid uncertainty. Ocean Eng 2024;307:118213.
7. Meng D, Yang S, de Jesus AMP, Zhu SP. A novel kriging-model-assisted reliability-based multidisciplinary design optimization strategy and its application in the offshore wind turbine tower. Renew Energy 2023;203:407-20.
8. Meng DB, Zhu SP. Multidisciplinary design optimization of complex structures under uncertainty. Boca Raton: CRC Press; 2024.
9. Nilsson J, Bertling L. Maintenance management of wind power systems using condition monitoring systems - life cycle cost analysis for two case studies. IEEE Trans On Energy Conver 2007;22:223-9.
10. Kusiak A, Verma A. A data-driven approach for monitoring blade pitch faults in wind turbines. IEEE Trans Sustain Energy 2010;2:87-96.
11. Gill S, Stephen B, Galloway S. Wind turbine condition assessment through power curve copula modeling. IEEE Trans Sustain Energy 2012;3:94-101.
12. Kusiak A, Verma A. Monitoring wind farms with performance curves. IEEE Trans Sustain Energy 2013;4:192-9.
13. Zaher A, Mcarthur SDJ, Infield DG, Patel Y. Online wind turbine fault detection through automated SCADA data analysis. Wind Energy 2009;12:574-93.
14. Garcia MC, Sanz-Bobi MA, del Pico J. SIMAP: intelligent system for predictive maintenance: application to the health condition monitoring of a windturbine gearbox. Comput Ind 2006;57:552-68.
15. Yang W, Court R, Jiang J. Wind turbine condition monitoring by the approach of SCADA data analysis. Renew Energy 2013;53:365-76.
16. Zhang S, Lang ZQ. SCADA-data-based wind turbine fault detection: a dynamic model sensor method. Control Eng Pract 2020;102:104546.
17. Zhang F, Wen Z, Liu D, Jiao J, Wan H, Zeng B. Calculation and analysis of wind turbine health monitoring indicators based on the relationships with SCADA data. Appl Sci 2020;10:410.
18. Tang M, Chen W, Zhao Q, et al. Development of an SVR model for the fault diagnosis of large-scale doubly-fed wind turbines using SCADA data. Energies 2019;12:3396.
19. Liu X, Du J, Ye ZS. A Condition monitoring and fault isolation system for wind turbine based on SCADA data. IEEE Trans Ind Inf 2022;18:986-95.
20. Velarde J, Mankar A, Kramhøft C, Sørensen JD. Probabilistic calibration of fatigue safety factors for offshore wind turbine concrete structures. Eng Struct 2020;222:111090.
21. Wang K, Ji C, Xue H, Tang W. Fatigue damage characteristics of a semisubmersible-type floating offshore wind turbine at tower base. J Renew Sustain Energy 2016;8:053307.
22. Fu B, Zhao J, Li B, et al. Fatigue reliability analysis of wind turbine tower under random wind load. Struct Saf 2020;87:101982.
23. Zhu D, Ding Z, Huang X, Li X. Probabilistic modeling for long-term fatigue reliability of wind turbines based on Markov model and subset simulation. Int J Fatigue 2023;173:107685.
24. Li M, Luo Y, Xie L, Tong C, Chen C. Fatigue reliability assessment method for wind power gear system based on multidimensional finite element method. J Risk Reliab 2024;238:540-58.
25. Liu Z, He Z, Tu L, Liu X, Liu H, Liang J. A fatigue reliability assessment approach for wind turbine blades based on continuous time Bayesian network and FEA. Qual Reliab Eng 2023;39:1603-21.
26. Horn JT, Leira BJ. Fatigue reliability assessment of offshore wind turbines with stochastic availability. Reliab Eng Syst Saf 2019;191:106550.
27. Liu G, Liu H, Zhu C, Mao T, Hu G. Design optimization of a wind turbine gear transmission based on fatigue reliability sensitivity. Front Mech Eng 2021;16:61-79.
28. Zhang Z, Zhou M, Fang M. First-passage probability analysis of Wiener process using different methods and its applications in the evaluation of structural durability degradation. Eur J Environ Civ Eng 2021;25:1763-81.
29. Roberts JB. First-passage probabilities for randomly excited systems: diffusion methods. Probabilist Eng Mech 1986;1:66-81.
30. Zhang Z, Liu M, Zhou M, Chen J. Dynamic reliability analysis of nonlinear structures using a Duffing-system-based equivalent nonlinear system method. Int J Approx Reason 2020;126:84-97.
31. Pastorcic D, Vukelic G, Bozic Z. Coil spring failure and fatigue analysis. Eng Fail Anal 2019;99:310-8.
32. Weibring M, Gondecki L, Tenberge P. Simulation of fatigue failure on tooth flanks in consideration of pitting initiation and growth. Tribol Int 2019;131:299-307.
33. Zhang Z, Liu X, Zhang Y, Zhou M, Chen J. Time interval of multiple crossings of the Wiener process and a fixed threshold in engineering. Mech Syst Signal Proc 2020;135:106389.
34. Zhang Z, Zhao C, Zhao Z, Wang F, Zhao B. Structural fatigue reliability evaluation based on probability analysis of the number of zero-crossings of stochastic response process. Eng Fail Anal 2023;143:106923.
35. Liu G, Gao K, Law SS. An improved sieve point method for the reliability analysis of structures. Probabilist Eng Mech 2020;62:103087.
36. National Standard of the People’s Republic of China. Standard for design of high-rising structures (GB50135-2019). Beijing: China Architecture Industry Press; 2019. Available from: https://www.gbstandards.org/GB_standard_english_3.asp?code=GB%2050135-2019&id=45634 [Last accessed on 26 Sep 2024].
37. Gao K, Liu G, Tang W. High-dimensional reliability analysis based on the improved number-theoretical method. Appl Math Model 2022;107:151-64.
38. Niu Q. New energy technologies-wind energy technology. Beijing: Science Press; 2009. Available from: https://ss.zhizhen.com/detail_38502727e7500f268a9ccc00f75bb01ccfc384332d18b1e11921b0a3ea25510134114c969f2eae5c8619c3781aeff6c1ed60753c1335db4b2ac4765c2ca0e502d2822a9bb48c12c32752f14c8ebc102a [Last accessed on 26 Sep 2024].
39. National Standard of the People’s Republic of China. Standard for design of steel structures (GB 50017-2017). Beijing: China Architecture & Building Press; 2017. Available from: https://www.chinesestandard.net/PDF.aspx/GB50017-2017 [Last accessed on 26 Sep 2024].
