Baseline model based structural health monitoring method under varying environment
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DOI: 10.1016/j.renene.2019.02.007
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References listed on IDEAS
- Elforjani, Mohamed & Bechhoefer, Eric, 2018. "Analysis of extremely modulated faulty wind turbine data using spectral kurtosis and signal intensity estimator," Renewable Energy, Elsevier, vol. 127(C), pages 258-268.
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- Alharthi, Majed & Hanif, Imran & Alamoudi, Hawazen, 2022. "Impact of environmental pollution on human health and financial status of households in MENA countries: Future of using renewable energy to eliminate the environmental pollution," Renewable Energy, Elsevier, vol. 190(C), pages 338-346.
- Hang, Xinyu & Zhu, Xiaoxun & Gao, Xiaoxia & Wang, Yu & Liu, Longhu, 2024. "Study on crack monitoring method of wind turbine blade based on AI model: Integration of classification, detection, segmentation and fault level evaluation," Renewable Energy, Elsevier, vol. 224(C).
- Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
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Keywords
Wind turbine; Varying environment; B-spline model; Structural health monitoring;All these keywords.
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