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Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET)
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Institute for Energy and Environment, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XQ, UK
* Author to whom correspondence should be addressed.
Received: 7 September 2012; in revised form: 29 November 2012 / Accepted: 30 November 2012 / Published: 14 December 2012
Abstract: With appropriate vibration modeling and analysis the incipient failure of key components such as the tower, drive train and rotor of a large wind turbine can be detected. In this paper, the Nonlinear State Estimation Technique (NSET) has been applied to model turbine tower vibration to good effect, providing an understanding of the tower vibration dynamic characteristics and the main factors influencing these. The developed tower vibration model comprises two different parts: a sub-model used for below rated wind speed; and another for above rated wind speed. Supervisory control and data acquisition system (SCADA) data from a single wind turbine collected from March to April 2006 is used in the modeling. Model validation has been subsequently undertaken and is presented. This research has demonstrated the effectiveness of the NSET approach to tower vibration; in particular its conceptual simplicity, clear physical interpretation and high accuracy. The developed and validated tower vibration model was then used to successfully detect blade angle asymmetry that is a common fault that should be remedied promptly to improve turbine performance and limit fatigue damage. The work also shows that condition monitoring is improved significantly if the information from the vibration signals is complemented by analysis of other relevant SCADA data such as power performance, wind speed, and rotor loads.
Keywords: wind turbine; tower vibration; SCADA data; nonlinear state estimation technique (NSET); modeling; blade asymmetry
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Cite This Article
MDPI and ACS Style
Guo, P.; Infield, D. Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET). Energies 2012, 5, 5279-5293.
Guo P, Infield D. Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET). Energies. 2012; 5(12):5279-5293.
Guo, Peng; Infield, David. 2012. "Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET)." Energies 5, no. 12: 5279-5293.