Robust fault estimation in wind turbine systems using GA optimisation

Odofin, Sarah, Gao, Zhiwei and Sun, Kai (2015) Robust fault estimation in wind turbine systems using GA optimisation. In: 13th IEEE Conference on Industrial Informatics (INDIN), 22 - 24 July 2015, Cambridge.

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Abstract

Wind turbine system is a safety-critical system, which
has the demand to improve the operating reliability and reducing the cost caused by the shut-down time and component repairing. As a result, condition monitoring and fault diagnosis have received much attention for wind turbine energy systems. Noticing that environmental disturbances are unavoidable, therefore how to improve the robustness of a fault diagnosis scheme against disturbances/noises has been a key issue in fault
diagnosis community. In this investigation, a robust fault
estimation approach with the aid of eigenstructure assignment and genetic algorithm (GA) optimization is presented so that the estimation error dynamics has a good robustness against disturbances. A simulation study is carried out for a 5MW wind turbine dynamic model, which has demonstrated the effectiveness of the proposed techniques.

Item Type:	Conference or Workshop Item (Lecture)
Subjects:	H100 General Engineering H600 Electronic and Electrical Engineering
Department:	Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User:	Dr Zhiwei Gao
Date Deposited:	19 Nov 2015 16:45
Last Modified:	12 Oct 2019 19:21
URI:	http://nrl.northumbria.ac.uk/id/eprint/24605

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