Fatigue Damage Evaluation of High-strength Bolt for Tower of Wind Turbine
DOI:
https://doi.org/10.13052/ejcm2642-2085.3363Keywords:
Wind turbine, tower cylinder flange, bolt, the equivalent fatigue stress, machine learningAbstract
Due to the particularity of wind resources and different wind conditions in different locations, wind turbines accumulate fatigue damage at different speeds, and the existing methods fail to provide accurate and personalized fatigue damage evaluation. A fatigue evaluation method based on machine learning was established based on the connection bolts of wind turbine tower flanges. GH Bladed software was used to simulate and calculate the load time data of normal power generation conditions under wind conditions with different parameter combination. Then, fatigue damage of bolts was obtained using Schmidt-Neuper algorithm, wind condition parameters-fatigue damage data set was established, and fatigue damage was converted into equivalent fatigue stress (EFS). The mapping model of wind condition parameters and EFS is established based on various machine learning algorithms, and the corresponding fatigue damage can be obtained according to any combination of wind condition parameters. The results demonstrate that XGBoost algorithm achieves the highest accuracy in fatigue damage evaluation.
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References
Kang J, Liu H, Fu D. Fatigue life and strength analysis of a main shaft-to-hub bolted connection in a wind turbine. Energies, 12(1): 7, 2018.
Alonso-Martinez M, Adam J M, Alvarez-Rabanal F P, et al. Wind turbine tower collapse due to flange failure: FEM and DOE analyses. Engineering Failure Analysis. 104: 932–949, 2019.
Yu Z, Sun P, Wang D. Fatigue life prediction for flange connecting bolts of wind turbine tower. Journal of Shanghai Jiaotong University (Science), 25: 526–530, 2020.
Lochan S, Mehmanparast A, Wintle J. A review of fatigue performance of bolted connections in offshore wind turbines. Procedia Structural Integrity, 17: 276–283, 2019.
Fu B, Zhao J, Li B, et al. Fatigue reliability analysis of wind turbine tower under random wind load. Structural Safety, 87: 101982, 2020.
Anup K C, Whale J, Evans S P, et al. An investigation of the impact of wind speed and turbulence on small wind turbine operation and fatigue loads. Renewable Energy, 146: 87-98, 2020.
Stensgaard Toft H, Svenningsen L, Moser W, et al. Wind climate parameters for wind turbine fatigue load assessment. Journal of Solar Energy Engineering, 138(3): 031010, 2016.
Leian Z, Xuemei H, Guangming Y. Fatigue life evaluation for wind turbine blade based on multistage loading accumulative damage theory. The Open Mechanical Engineering Journal, 9(1), 2015.
Mendez Reyes H, Kanev S, Doekemeijer B, et al. Validation of a lookup-table approach to modeling turbine fatigue loads in wind farms under active wake control. Wind Energy Science, 4(4): 549–561, 2019.
Teixeira R, O’Connor A, Nogal M, et al. Analysis of the design of experiments of offshore wind turbine fatigue reliability design with Kriging surfaces. Procedia Structural Integrity, 5: 951-958, 2017.
Murcia J P, Réthoré P E, Dimitrov N, et al. Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates. Renewable Energy, 119: 910–922, 2018.
Wilkie D, Galasso C. Gaussian process regression for fatigue reliability analysis of offshore wind turbines. Structural Safety, 88: 102020, 2021.
Li X, Zhang W. Long-term fatigue damage assessment for a floating offshore wind turbine under realistic environmental conditions. Renewable Energy, 159: 570–584, 2020.
Weijtjens W, Stang A, Devriendt C, et al. Bolted ring flanges in offshore-wind support structures-in-situ validation of load-transfer behaviour. Journal of Constructional Steel Research, 176: 106361, 2021.
Liu M, Geng R, Wang J, et al. The Investigation of Various Flange Gaps on Wind Turbine Tower Bolt Fatigue Using Finite-Element Method. Applied Sciences, 14(9): 3670, 2024.
