A master thesis from Aalborg University
A Novel Approach for Fault Diagnosis of Hydraulic Pitch Systems in Wind Turbines
Author(s)
Term
4. term
Education
Publication year
2016
Submitted on
2016-06-01
Pages
215 pages
Abstract
ThisMaster’s Thesis investigates fault detection and diagnosis (FDD) in a hydraulic pitch system by applying artificial neural networks (ANN). A mathematical model of the pitch system is developed and the parametrisation of the model is conducted based on experiments. The model is applied for development and testing of several FDD schemes, which are used to evaluate which experimental tests are necessary to perform. A test rig including the main components of the pitch system is constructed in a manner that allows emulation of leakage faults. The test rig allows for general evaluation of the developed FDD scheme. The main conclusion states that a model-based scheme with diagnosis by a focused time-delay ANN shows theoretical superior performance. This is tested on the test rig to validate the scheme. The main results show a decrease of estimation accuracy of leakages when applied on the actual system, however, a stuck servo valve and a pressure transducer failure are successfully diagnosed.
Keywords
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