Date of Award

2010

Publication Type

Master Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

First Advisor

Ting, David (Mechanical, Automotive and Materials Engineering)

Keywords

Engineering, Mechanical.

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

Structural health monitoring (SHM) is a process of implementing a damage detection strategy for a mechanical system. Wind turbine machinery stands to benefit from SHM significantly as the ability to detect early stages of damage before serious malfunction or collapse reduces the overall operating costs of wind power projects. This study presents the development of vibration based wind turbine structural health monitoring through experimental analysis of an operating wind turbine. A database of acquired vibration response signals detailing 3 hours of turbine operation was assembled and a Daubachies 6th order wavelet was used to perform a 12 level discrete wavelet decomposition such that general trends and patterns within the signals could be identified. A novel vibration based SHM scheme is developed based on findings from experimental work. With further development this vibration scheme can be applied by wind farm operators to reduce downtime and failure frequency of utility scale wind turbines.

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