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PDF of thesis T15079 PDF of thesis T15079 - (5 M)
Title Condition monitoring of wind turbines using micro-doppler information / Zijian Guo.
Name Guo, Zijian. .
Abstract With the development of modern science technology and awareness of environmental protection, new wnergy technologies have emerged and developed rapidly. Wind power, as a renewable energy source, has played a pivotal role in society which has been deeply researched and promoted around the world in recent years. As wind turbin capacity is gowing, wind turbine blade maintenance test and diagnosis have gradually drawn people's attention, also have become hot points in new energy technologies. Therefore, exploring the development of wind turbine blade detaction and diagnosis is necessary.
Abstract This thesis will adopt radar technology to monitor and diagnose the operation of the wind turbine blade, with a simple and effective way to solve the working condition of wind turbine blades. This study focuses on the design of a running model of wind turbine, within-depth analysis of micro-doppler of radar back scattering signals from wind turbine blades to determine the health of the wind turbine blades, providing the basic data for the maintenance of the wind turbine blades.
Abstract Monitor and diagnosis of the whole process is devided into four parts - Theory Analysis, Mathematical Modeling, Algorithm Development and Experimental Design. The thesis will focus on the wind turbine blade daily operation problems -- vibration, corrosion, and other problems, through the data model analysis, to give a more efficient and accurate detection and diagnosis, to provide a remote and online protection for the safe operation of wind turbine blades.
Publication date 2017.
Name Soraghan, John, degree supervisor.
Name University of Strathclyde. Department of Electronic and Electrical Engineering.
Name University of Strathclyde. Department of Electronic and Electrical Engineering. Centre for Signal and Image Processing.
Thesis note Thesis M. Phil. University of Strathclyde 2017 T15079

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