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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Radar-based sensing of wind turbines blades based on 35 GHz FMCW sensors installed at operational wind turbine towers

Authors: Mälzer, Moritz; Beck, Sebastian; Moll, Jochen;

Radar-based sensing of wind turbines blades based on 35 GHz FMCW sensors installed at operational wind turbine towers

Abstract

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.

{"references": ["M\u00e4lzer, M.; Beck, S.; Alipek, S.; Reichart, E.; Moll, J.; Krozer, V.; Oikonomopoulos, C.; Kassner, J.; H\u00e4gelen, M.; Heinecke, T.; Cerbe, B.; Rose, J.; Klumpp, V.; Berger, M. & Kohl, M., Radar-based structural monitoring of wind turbines blades: Field results from two operational wind turbines, 14th International Workshop on Structural Health Monitoring, 2023, pp. 2653-2660"]}

The authors gratefully acknowledge the financial support of this research by the Federal Ministry for Economic Affairs and Climate Action (grant number: 03EE2035A).

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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