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The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including those from the School of Psychological Sciences & Health - but also papers by researchers based within the Faculties of Science, Engineering, Humanities & Social Sciences, and from the Strathclyde Business School.

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Model-based fault detection and isolation for wind turbine

Hwas, Abdulhamed Moh Suliman and Katebi, Reza (2012) Model-based fault detection and isolation for wind turbine. In: Proceedings of the 2012 UKACC International Conference on Control (CONTROL). IEEE, pp. 876-881. ISBN 978-1-4673-1559-3

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Abstract

In this paper, a quantitative model based method is proposed for early fault detection and diagnosis of wind turbines. The method is based on designing an observer using a model of the system. The observer innovation signal is monitored to detect faults. For application to the wind turbines, a first principles nonlinear model with pitch angle and torque controllers is developed for simulation and then a simplified state space version of the model is derived for design. The fault detection system is designed and optimized to be most sensitive to system faults and least sensitive to system disturbances and noises. A multiobjective optimization method is then employed to solve this dual problem. Simulation results are presented to demonstrate the performance of the proposed method.