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A Vibration Estimation Method for Wind Turbine Blades
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Tekniska sektionen, Institutionen för teknikvetenskaper, Elektricitetslära.
Tokyo Inst Technol, Dept Mech & Aerosp Engn, Tokyo, Japan..
Tokyo Inst Technol, Dept Mech & Aerosp Engn, Tokyo, Japan..
Vise andre og tillknytning
2017 (engelsk)Inngår i: Experimental mechanics, ISSN 0014-4851, E-ISSN 1741-2765, Vol. 57, nr 8, s. 1213-1224Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This paper reports the development of a vibration monitoring system for wind turbine blades. This system is used to estimate the deflection at the tip blade on a wind turbine tower. Technical accidents of wind turbine blades have become increasingly common. Thus, regular monitoring of the blades is very important to prevent breakdowns, especially in cases when the blades begin to vibrate excessively. The monitoring system developed in this study satisfies two main objectives for practicality. First, our system is easy to install on existing wind turbines. Second, blade deflection is measured in real time. Our system can be operated using a few strain gages attached at the blade root, and the deflection is calculated based on the monitored stress. Thus, direct measurement of deflection at the blade tip is unnecessary. An estimation algorithm for this purpose is adopted based on the experimental modal analysis. This paper focuses on the evaluation of the estimation algorithm to investigate the feasibility of our system. Basic experiments were conducted using a simple blade model of a 300 W scaled wind turbine under rotation. Signals from the strain gages were acquired by a sensor network and sent to a computer through a wireless connection. The results show that the estimation accuracy is acceptably high. Therefore, we conclude that our proposed system is practical.

sted, utgiver, år, opplag, sider
2017. Vol. 57, nr 8, s. 1213-1224
Emneord [en]
Wind turbine blade, Vibration estimation, Modal analysis, Strain gage
HSV kategori
Identifikatorer
URN: urn:nbn:se:uu:diva-336294DOI: 10.1007/s11340-017-0295-xISI: 000410887100005OAI: oai:DiVA.org:uu-336294DiVA, id: diva2:1176892
Tilgjengelig fra: 2018-01-23 Laget: 2018-01-23 Sist oppdatert: 2018-01-23bibliografisk kontrollert

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