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Proceedings Paper

Automated wind load characterization of wind turbine structures by embedded model updating
Author(s): R. Andrew Swartz; Andrew T. Zimmerman; Jerome P. Lynch
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Paper Abstract

The continued development of renewable energy resources is for the nation to limit its carbon footprint and to enjoy independence in energy production. Key to that effort are reliable generators of renewable energy sources that are economically competitive with legacy sources. In the area of wind energy, a major contributor to the cost of implementation is large uncertainty regarding the condition of wind turbines in the field due to lack of information about loading, dynamic response, and fatigue life of the structure expended. Under favorable circumstances, this uncertainty leads to overly conservative designs and maintenance schedules. Under unfavorable circumstances, it leads to inadequate maintenance schedules, damage to electrical systems, or even structural failure. Low-cost wireless sensors can provide more certainty for stakeholders by measuring the dynamic response of the structure to loading, estimating the fatigue state of the structure, and extracting loading information from the structural response without the need of an upwind instrumentation tower. This study presents a method for using wireless sensor networks to estimate the spectral properties of a wind turbine tower loading based on its measured response and some rudimentary knowledge of its structure. Structural parameters are estimated via model-updating in the frequency domain to produce an identification of the system. The updated structural model and the measured output spectra are then used to estimate the input spectra. Laboratory results are presented indicating accurate load characterization.

Paper Details

Date Published: 31 March 2010
PDF: 12 pages
Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 76470J (31 March 2010); doi: 10.1117/12.847697
Show Author Affiliations
R. Andrew Swartz, Michigan Technological Univ. (United States)
Andrew T. Zimmerman, Univ. of Michigan (United States)
Jerome P. Lynch, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 7647:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010
Masayoshi Tomizuka, Editor(s)

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