Simulation Study of Fault Detection and Diagnosis for Wind Turbine System

Odofin, Sarah, Kai, Sun, Gao, Zhiwei and Ghassemlooy, Zabih (2014) Simulation Study of Fault Detection and Diagnosis for Wind Turbine System. In: 15th Annual Postgraduate Symposium on the Convergence of Telecommunications, Network and Broadcasting, 23rd - 24th June 2014, Liverpool, UK.

Full text not available from this repository. (Request a copy)
Official URL:


This paper presents a quantitative review of early detection and estimation of fault for wind turbine system. The model-based technique is proposed to provide an assessment of all possible faults for renewable energy sources. The augmented observer is applied to estimate the real physical data of the system sensor faults and states simultaneously. The fault detection and diagnosis is designed to be most sensitive to faults and states of wind turbine system. A mathematical example is specified to exhibit the dynamic system behavior for the wind turbine model to validate the competence of the system performance. The state space is used to explain the design. The satisfactory fault diagnosis performance is demonstrated in the simulation results.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Condition monitoring, fault detection, fault diagnosis, augmented observer, fault estimation, wind turbine
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Paul Burns
Date Deposited: 23 Sep 2014 09:57
Last Modified: 12 Oct 2019 19:20

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics