Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.665217
Title: Model-based fault detection and isolation techniques for wind turbines
Author: Hwas, Abdulhamed
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2013
Availability of Full Text:
Access through EThOS:
Access through Institution:
Abstract:
The main objective of the work of this thesis is to design model-based fault detection and isolation techniques for a large-scale wind turbine. A mathematical model of the 5MW wind turbine was developed; the model was sufficiently detailed to be used for simulation purposes. The stages of the modelling procedure were to divide the overall wind turbine system into appropriate sub-models suitable for separate modelling. Each sub-model was then presented and combined in order to obtain a completed non-linear wind turbine model. Two methods are proposed to calculate the gains of a proportional-integral (PI) pitch angle controller for the non-linear model: the first method is analytical and the second method is based on simulation. The simulation results demonstrated good performance for both proposed PI schemes. In order to design an electrical torque controller, an internal model controlbased PI controller was used to find the gains of the current and of the torque controller; good static and dynamic performance were achieved. In this thesis, a quantitative model-based method for early detection and diagnosis of wind turbine faults is proposed. The method is based on designing an observer by using a linear model of the system; the observer innovation signal is monitored to detect faults. The fault detection system was designed and optimised to be maximally sensitive to system faults and minimally sensitive to system disturbances and noise; a multi-objective optimisation method was utilised to address this dual problem. Simulation results are presented to demonstrate the performance of the proposed method. Next, a non-linear observer-based scheme for early fault detection and isolation of wind turbines was developed. The method is based on designing a nonlinear observer using a non-linear model of the wind turbine. The state-dependent differential Riccati equation was used to design a non-linear observer. The comparison of system outputs with non-linear observer estimation confirmed good performance of the non-linear observer. Based on the non-linear observer, a residual generator for monitoring wind turbine model was formulated. Simulation results illustrated that the proposed method is a robust method in detecting and isolating a single fault or multi-faults in wind turbine sensors.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.665217  DOI: Not available
Share: