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• W2970058415 abstract "Wind energy is the inexhaustible renewable energy source, and the number of wind power utilization in many countries is also growing rapidly. Wind turbine works in harsh natural environment, and long-term random wind load will cause tremendous damage on the internal gear transmission system. In order to accurately predict the fatigue reliability for a 5 MW large-scale wind power gear transmission system in service, a detailed system simulation model is established, and the accurate stress calculation is carried out for the contact fatigue failure mode on tooth surface. In this paper, the linear relationship between the input torque of gear system and the maximum contact stress of each gear is established, and the load history conversion between the input torque and the contact stress can be realized. Then the Miner cumulative damage theory is used to transform the complex random stress history into equivalent constant amplitude cyclic stress, which is load input variable for the reliability prediction model. At the same time, a contact fatigue test for tooth surface is carried out, and P-S-N curves of the gear samples with specific parameters are obtained, which is the strength input variable for the reliability prediction model. In order to reflect the uncertainty effect of service load on the reliability of gear transmission system, the randomness of load history is expressed complementarily at macro level and micro level, respectively. The traditional stress and strength interference theory is extended, and the reliability model of series system considering the statistical dependence among part failures is established. Finally, the advantage of the proposed model is demonstrated by comparing the prediction result of the new model with that of the traditional model." @default.
• W2970058415 created "2019-09-05" @default.
• W2970058415 creator A5074024151 @default.
• W2970058415 date "2020-01-01" @default.
• W2970058415 modified "2023-10-01" @default.
• W2970058415 title "Load characteristic analysis and fatigue reliability prediction of wind turbine gear transmission system" @default.
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• W2970058415 doi "https://doi.org/10.1016/j.ijfatigue.2019.105259" @default.
• W2970058415 hasPublicationYear "2020" @default.
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