In Situ Structural Health Monitoring of Full-Scale Wind Turbine Blades in Operation Based on Stereo Digital Image Correlation
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Khazaee, Meghdad & Derian, Pierre & Mouraud, Anthony, 2022. "A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods," Renewable Energy, Elsevier, vol. 199(C), pages 1568-1579.
- Zheng Liu & Xin Liu & Kan Wang & Zhongwei Liang & José A.F.O. Correia & Abílio M.P. De Jesus, 2019. "GA-BP Neural Network-Based Strain Prediction in Full-Scale Static Testing of Wind Turbine Blades," Energies, MDPI, vol. 12(6), pages 1-15, March.
- Han Peng & Songyin Li & Linjian Shangguan & Yisa Fan & Hai Zhang, 2023. "Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research," Sustainability, MDPI, vol. 15(10), pages 1-35, May.
- Bingchuan Sun & Hongmei Cui & Zhongyang Li & Teng Fan & Yonghao Li & Lida Luo & Yong Zhang, 2022. "Experimental Study on the Noise Evolution of a Horizontal Axis Icing Wind Turbine Based on a Small Microphone Array," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
- Chandrasekhar, Kartik & Stevanovic, Nevena & Cross, Elizabeth J. & Dervilis, Nikolaos & Worden, Keith, 2021. "Damage detection in operational wind turbine blades using a new approach based on machine learning," Renewable Energy, Elsevier, vol. 168(C), pages 1249-1264.
- Luo, Kai & Chen, Liang & Liang, Wei, 2022. "Structural health monitoring of carbon fiber reinforced polymer composite laminates for offshore wind turbine blades based on dual maximum correlation coefficient method," Renewable Energy, Elsevier, vol. 201(P1), pages 1163-1175.
- Wang, Zixuan & Qin, Bo & Sun, Haiyue & Zhang, Jian & Butala, Mark D. & Demartino, Cristoforo & Peng, Peng & Wang, Hongwei, 2023. "An imbalanced semi-supervised wind turbine blade icing detection method based on contrastive learning," Renewable Energy, Elsevier, vol. 212(C), pages 251-262.
- Tang, Yaochi & Chang, Yunchi & Li, Kuohao, 2023. "Applications of K-nearest neighbor algorithm in intelligent diagnosis of wind turbine blades damage," Renewable Energy, Elsevier, vol. 212(C), pages 855-864.
- Sikandar Khan, 2023. "A Modeling Study Focused on Improving the Aerodynamic Performance of a Small Horizontal Axis Wind Turbine," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
- Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Condition monitoring of wind turbine blades based on self-supervised health representation learning: A conducive technique to effective and reliable utilization of wind energy," Applied Energy, Elsevier, vol. 313(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Sun, Shilin & Li, Qi & Hu, Wenyang & Liang, Zhongchao & Wang, Tianyang & Chu, Fulei, 2023. "Wind turbine blade breakage detection based on environment-adapted contrastive learning," Renewable Energy, Elsevier, vol. 219(P2).
- Paweł Knes & Phong B. Dao, 2024. "Machine Learning and Cointegration for Wind Turbine Monitoring and Fault Detection: From a Comparative Study to a Combined Approach," Energies, MDPI, vol. 17(20), pages 1-21, October.
- Wang, Shun & Vidal, Yolanda & Pozo, Francesc, 2026. "Recent advances in wind turbine condition monitoring using SCADA data: A state-of-the-art review," Reliability Engineering and System Safety, Elsevier, vol. 267(PA).
- Tian, Runze & Kou, Peng & Zhang, Yuanhang & Mei, Mingyang & Zhang, Zhihao & Liang, Deliang, 2024. "Residual-connected physics-informed neural network for anti-noise wind field reconstruction," Applied Energy, Elsevier, vol. 357(C).
- Wang, Anqi & Pei, Yan & Qian, Zheng & Zareipour, Hamidreza & Jing, Bo & An, Jiayi, 2022. "A two-stage anomaly decomposition scheme based on multi-variable correlation extraction for wind turbine fault detection and identification," Applied Energy, Elsevier, vol. 321(C).
- Xu, Xuefang & Li, Bo & Qiao, Zijian & Shi, Peiming & Shao, Huaishuang & Li, Ruixiong, 2023. "Caputo-Fabrizio fractional order derivative stochastic resonance enhanced by ADOF and its application in fault diagnosis of wind turbine drivetrain," Renewable Energy, Elsevier, vol. 219(P1).
- Ye, Feng & Ezzat, Ahmed Aziz, 2024. "Icing detection and prediction for wind turbines using multivariate sensor data and machine learning," Renewable Energy, Elsevier, vol. 231(C).
- Lorin Jenkel & Stefan Jonas & Angela Meyer, 2023. "Privacy-Preserving Fleet-Wide Learning of Wind Turbine Conditions with Federated Learning," Energies, MDPI, vol. 16(17), pages 1-29, September.
- Sun, Shilin & Wang, Tianyang & Chu, Fulei, 2022. "In-situ condition monitoring of wind turbine blades: A critical and systematic review of techniques, challenges, and futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
- Phong B. Dao, 2023. "On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data," Energies, MDPI, vol. 16(5), pages 1-17, March.
- Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
- Ali Zabihi & Farhood Aghdasi & Chadi Ellouzi & Nand Kishore Singh & Ratneshwar Jha & Chen Shen, 2024. "Non-Contact Wind Turbine Blade Crack Detection Using Laser Doppler Vibrometers," Energies, MDPI, vol. 17(9), pages 1-14, May.
- Mofeoluwa Oyekan & Joy Onma Enyejo, 2023. "Harnessing Data Analytics to Maximize Renewable Energy Asset Performance," International Journal of Scientific Research and Modern Technology, Prasu Publications, vol. 2(8), pages 64-80.
- Tang, Yaochi & Chang, Yunchi & Li, Kuohao, 2023. "Applications of K-nearest neighbor algorithm in intelligent diagnosis of wind turbine blades damage," Renewable Energy, Elsevier, vol. 212(C), pages 855-864.
- Mohamed Benbouzid & Tarek Berghout & Nur Sarma & Siniša Djurović & Yueqi Wu & Xiandong Ma, 2021. "Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review," Energies, MDPI, vol. 14(18), pages 1-33, September.
- Peng, Mengyao & Hui, Yi & Yang, Qingshan & Liu, Gang & Law, Siu-Seong, 2025. "Modal analysis of mistuned wind turbine induced by blade local damage using continuum mathematical model," Renewable Energy, Elsevier, vol. 252(C).
- Luo, Kai & Chen, Liang & Liang, Wei, 2022. "Structural health monitoring of carbon fiber reinforced polymer composite laminates for offshore wind turbine blades based on dual maximum correlation coefficient method," Renewable Energy, Elsevier, vol. 201(P1), pages 1163-1175.
- Ma, Deyin & Zhang, Lizhi & Sun, Bo, 2021. "An interval scheduling method for the CCHP system containing renewable energy sources based on model predictive control," Energy, Elsevier, vol. 236(C).
- Xing Su & Xudong Wang & Wanli Xu & Liqian Yuan & Chunhua Xiong & Jinmao Chen, 2024. "Offshore Wind Power: Progress of the Edge Tool, Which Can Promote Sustainable Energy Development," Sustainability, MDPI, vol. 16(17), pages 1-22, September.
- Zhu, Yunlong & Dong, Zhe & Cheng, Zhonghua & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2023. "Neural network extended state-observer for energy system monitoring," Energy, Elsevier, vol. 263(PA).
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13783-:d:1240811. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13783-d1240811.html