Detection of faulty high speed wind turbine bearing using signal intensity estimator technique

Wind Energy ◽  
2017 ◽  
Vol 21 (1) ◽  
pp. 53-69 ◽  
Author(s):  
Mohamed Elforjani ◽  
Suliman Shanbr ◽  
Eric Bechhoefer
Keyword(s):  
Wind Turbine ◽  
Signal Intensity ◽  
High Speed ◽  
Turbine Bearing ◽  
Intensity Estimator

Aerodynamic and aeroacoustic performance investigations on modified H-rotor Darrieus wind turbine

2021 ◽  
pp. 0309524X2110039
Author(s):  
Amgad Dessoky ◽  
Thorsten Lutz ◽  
Ewald Krämer
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Cfd Simulation ◽  
Vertical Axis ◽  
3D Models ◽  
Power Coefficient ◽  
Design Parameters ◽  
Second Phase ◽  
Vertical Axis Wind Turbine ◽  
Guide Vanes

The present paper investigates the aerodynamic and aeroacoustic characteristics of the H-rotor Darrieus vertical axis wind turbine (VAWT) combined with very promising energy conversion and steering technology; a fixed guide-vanes. The main scope of the current work is to enhance the aerodynamic performance and assess the noise production accomplished with such enhancement. The studies are carried out in two phases; the first phase is a parametric 2D CFD simulation employing the unsteady Reynolds-averaged Navier-Stokes (URANS) approach to optimize the design parameters of the guide-vanes. The second phase is a 3D CFD simulation of the full turbine using a higher-order numerical scheme and a hybrid RANS/LES (DDES) method. The guide-vanes show a superior power augmentation, about 42% increase in the power coefficient at λ = 2.75, with a slightly noisy operation and completely change the signal directivity. A remarkable difference in power coefficient is observed between 2D and 3D models at the high-speed ratios stems from the 3D effect. As a result, a 3D simulation of the capped Darrieus turbine is carried out, and then a noise assessment of such configuration is assessed. The results show a 20% increase in power coefficient by using the cap, without significant change in the noise signal.

scholarly journals Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

2021 ◽  
Author(s):  
Baher Azzam ◽  
Ralf Schelenz ◽  
Björn Roscher ◽  
Abdul Baseer ◽  
Georg Jacobs
Keyword(s):  
Time Series ◽  
Wind Turbine ◽  
High Speed ◽  
Time Series Data ◽  
Development Trend ◽  
Series Data ◽  
Ann Model ◽  
Wind Turbine Gearbox ◽  
Virtual Sensor ◽  
Artificial Neural

AbstractA current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

Design and performance evaluation of vertical axis wind turbine for wind energy harvesting at railway

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hashwini Lalchand Thadani ◽  
Fadia Dyni Zaaba ◽  
Muhammad Raimi Mohammad Shahrizal ◽  
Arjun Singh Jaj A. Jaspal Singh Jaj ◽  
Yun Ii Go
Keyword(s):  
Wind Speed ◽  
Energy Harvesting ◽  
Wind Energy ◽  
Wind Turbine ◽  
High Speed ◽  
Vertical Axis ◽  
Speed Ratio ◽  
Vertical Axis Wind Turbine ◽  
Modeling Tools ◽  
Content Type

PurposeThis paper aims to design an optimum vertical axis wind turbine (VAWT) and assess its techno-economic performance for wind energy harvesting at high-speed railway in Malaysia.Design/methodology/approachThis project adopted AutoCAD and ANSYS modeling tools to design and optimize the blade of the turbine. The site selected has a railway of 30 km with six stops. The vertical turbines are placed 1 m apart from each other considering the optimum tip speed ratio. The power produced and net present value had been analyzed to evaluate its techno-economic viability.FindingsComputational fluid dynamics (CFD) analysis of National Advisory Committee for Aeronautics (NACA) 0020 blade has been carried out. For a turbine with wind speed of 50 m/s and swept area of 8 m2, the power generated is 245 kW. For eight trains that operate for 19 h/day with an interval of 30 min in nonpeak hours and 15 min in peak hours, total energy generated is 66 MWh/day. The average cost saved by the train stations is RM 16.7 mil/year with battery charging capacity of 12 h/day.Originality/valueWind energy harvesting is not commonly used in Malaysia due to its low wind speed ranging from 1.5 to 4.5 m/s. Conventional wind turbine requires a minimum cut-in wind speed of 11 m/s to overcome the inertia and starts generating power. Hence, this paper proposes an optimum design of VAWT to harvest an unconventional untapped wind sources from railway. The research finding complements the alternate energy harvesting technologies which can serve as reference for countries which experienced similar geographic constraints.

scholarly journals Fault diagnosis of wind turbine bearing using wireless sensor networks

2017 ◽  
Vol 21 (suppl. 2) ◽  
pp. 523-531 ◽  
Author(s):  
Indhu Ramalingam ◽  
Sankaran Annamalai ◽  
Sugumaran Vaithiyanathan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wireless Sensor ◽  
Turbine Bearing

scholarly journals Investigation of Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

2019 ◽  
Author(s):  
David Vaes ◽  
Yi Guo ◽  
Pietro Tesini ◽  
Jonathan A Keller
Keyword(s):  
Wind Turbine ◽  
High Speed ◽  
Wind Turbine Gearbox
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