Results 141 to 150 of about 3,881 (222)

Fault Detection for Wind Turbine Blade Bolts Based on GSG Combined with CS-LightGBM. [PDF]

Sensors (Basel), 2022
Tang M, Meng C, Wu H, Zhu H, Yi J, Tang J, Wang Y.   +6 more
europepmc   +1 more source

Multimodal dataset for wind turbine blade monitoring during lightning strikes. [PDF]

Sci Data
Li T, Li C, Qin Y, Tan L, Jiang B, Deng H.   +5 more
europepmc   +1 more source

Image Recognition of Wind Turbine Blade Defects Using Attention-Based MobileNetv1-YOLOv4 and Transfer Learning. [PDF]

Sensors (Basel), 2022
Zhang C, Yang T, Yang J.
europepmc   +1 more source

A comparative multi-objective investigation for metallic and non-metallic materials on the erosion resistance of wind turbine blade with performance evaluation. [PDF]

Sci Rep
Abou Taleb ASA, Abdelgaliel IH, Aly MF.
europepmc   +1 more source

The Springer Model for Lifetime Prediction of Wind Turbine Blade Leading Edge Protection Systems: A Review and Sensitivity Study. [PDF]

Materials (Basel), 2022
Hoksbergen N, Akkerman R, Baran I.
europepmc   +1 more source

Computational Analysis of a Wind Turbine Blade for Different Advanced Materials. [PDF]

Materials (Basel)
Fragkos PF, Theotokoglou EE.
europepmc   +1 more source

The Role of Orientation and Temperature on the Mechanical Properties of a 20 Years Old Wind Turbine Blade GFR Composite. [PDF]

Polymers (Basel), 2021
Ahmed MMZ, Alzahrani B, Jouini N, Hessien MM, Ataya S.   +4 more
europepmc   +1 more source

Performance Analysis of Reinforced Epoxy Functionalized Carbon Nanotubes Composites for Vertical Axis Wind Turbine Blade. [PDF]

Polymers (Basel), 2021
Elhenawy Y, Fouad Y, Marouani H, Bassyouni M.   +3 more
europepmc   +1 more source

Turbine-to-Textile: Upcycling Wind Turbine Blade Waste into High-Performance PAN Composite Fibers. [PDF]

ACS Appl Polym Mater
Thippanna V, Sun X, Sobczak MT, Ramanathan A, Theobald TG, Doran I, Were J, Yang L, Jaraczewski J, Casey J, Klepov VV, Liang L, Nolet S, Mada Kannan AN, Xu X, Song K.   +15 more
europepmc   +1 more source

Wind Turbine Blade Defect Recognition Method Based on Large-Vision-Model Transfer Learning. [PDF]

Sensors (Basel)
Li X, Tian J, Pang X, Shen L, Li H, Zheng Z.   +5 more
europepmc   +1 more source