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4 results for “turbine towers”
Radar-based sensing of wind turbines blades based on 35 GHz FMCW sensors installed at operational wind turbine towers
<p>The dataset contains radar-based measurements of rotor blades from three operational wind turbines as part of a structural health monitoring system. For this purpose, a sensor box with a 35 GHz radar sensor (about 1 000 measurements per second) and a camera system (about 100 images per second), is mounted on each wind turbine tower at approximately 100 m height. In order to distinguish individual rotor blades, a machine-readable marker printed on a self-adhesive film was applied on the blade’s surface. When a rotor blade passes the sensor, the camera captures an image of the marker while the radar records a measurement. The marker is then identified and the recorded data is assigned to a particular rotor blade. The measurements demonstrate that the damage detection methodology can be transferred to an image processing problem. The challenge is to manage the strong influence from variable environmental and operational conditions, e.g. wind speed, azimuth orientation, that modify the rotor blade appearance in the radargram significantly. The dataset contains measurements from the intact turbine blade conditions, because it was not possible to introduce structural damage.</p>
Data from: Effect of tower base painting on willow ptarmigan collision rates with wind turbines
<p>1. Birds colliding with turbine rotor blades is a well-known negative consequence of wind-power plants. However, there has been far less attention to the risk of birds colliding with the turbine towers, and how to mitigate this risk. 2. Based on data from the Smøla wind-power plant in Central Norway, it seems highly likely that willow ptarmigan (the only gallinaceous species found on the island) is prone to collide with turbine towers. By employing a BACI-approach, we tested if painting the lower parts of turbine towers black would reduce the collision risk. 3. Overall, there was a 48% reduction in the number of recorded ptarmigan carcasses per search at painted turbines relative to neighbouring control (unpainted) ones, with significant variation both within and between years. 4. Using contrast painting to the turbine towers resulted in significantly reduced number of ptarmigan carcasses found, emphasizing the effectiveness of such a relatively simple mitigation measure.</p>
Data from: Effect of tower base painting on willow ptarmigan collision rates with wind turbines
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NREL 5MW wind turbine blade and tower degradation
<p><strong>Problem</strong></p><p>➔Track the degradation of one rotor blade and tower base over over as 10 months period under wind inflow and operational uncertainties</p><p><strong>Scenario</strong></p><p>➔Continuous wind turbine blade and tower stiffness degradation, emulating blade root delamination resulting in dynamic instability, leading to the tower base excess fatigue.</p><p><strong>Simulation environment and setup in FAST v8 :</strong></p><p>➔In the blade input file: modify flap and edge stiffnesses in damage regions, blade root (only 1 in 3 blades is affected). Assumed equal degradation in both edgewise and flapwise directions</p><p>➔In the blade input file: modify mode shapes coefficients (1st flap, 2nd flap and 1st edge modes)</p><p>➔In the tower input file: modify FA and SS stiffnesses in damage regions, tower base</p><p>➔In the tower input file: modify mode shapes coefficients (1st & 2nd FA and 1st & 2nd SS modes)</p><p>➔Note that the tower degradation only "shows up" in the last 2 monitoring periods</p><p>➔In the turbulence input file: modify wind speed, tuburlence intensity, shear exponent, horizontal and vertical inflow angles.</p><p>➔Further complication by assuming that the average input environmental conditions are not stationary over the monitoring period, emulating seasonal variations.</p><p>➔This means 120 environmental samples (and consequenly input wind field time series) are sampled from different distributions each period during the degradation process</p>
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