Due to the rapid depletion of fossil fuel reserves and the intensification of problems associated with global warming, humanity is increasingly focusing on renewable energy sources. They have become not only an essential component of modern energy systems but also a foundation for the sustainable development of the future. Wind energy, as one of the most accessible sources of renewable energy, is attracting growing interest from both governments of developed countries and private investors. Modern wind turbines are becoming progressively larger, and their blades, which are key components for energy generation, are continually subjected to damage caused by the aggressive influence of the external environment and cyclic (i.e., time-varying) loads. Consequently, the issues of reliability and safety are paramount for ensuring the uninterrupted supply of electricity to both the population and businesses. To effectively monitor the condition of wind turbines, and particularly their blades, it is necessary to employ information technologies that enable precise and timely detection of potential failures and optimize maintenance processes 1. The paper analyses and synthesizes a classification of general methods and tools for determining the remaining service life of components subjected to cyclic loads. The concept of a model for predicting the residual service life of the wind turbine blade root is described in detail. Test input data were generated using modern professional software packages for wind turbine dynamics modelling such as OpenFAST and TurbSim. The detailed description of the proposed solution architecture and a flowchart of the developed method algorithm for fatigue assessment of the cross-sectional sectors of the 5 MW wind turbine blade root are provided. The algorithm employs the rainflow counting method and the Palmgren – Miner hypothesis of linear damage accumulation. Based on these foundations software module was developed to implement the proposed model and the obtained results make it possible, at a first approximation, allow predicting the fatigue life of the root of a wind turbine blade after simulated dynamic loads.
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O. A. Basalkevych
D. V. Rudavs’kyi
Ukrainian Journal of Information Technology
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Basalkevych et al. (Wed,) studied this question.
www.synapsesocial.com/papers/68d44a3031b076d99fa530ad — DOI: https://doi.org/10.23939/ujit2025.01.045