Imaging-based fault detection of wind turbines

With the development of renewable energy, the wind-energy generation is no longer a brand-new field. Considering the complex work environment and huge maintenance fee, windmill detection plays a significant role in the wind industry. Therefore, combining with the application of digital image technol...

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Bibliographic Details
Main Author:	Yu, Songyang
Other Authors:	Zhang, Yang
Published:	University of Sheffield 2018
Subjects:	621
Online Access:	https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755167

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spelling	ndltd-bl.uk-oai-ethos.bl.uk-7551672019-03-05T15:39:32ZImaging-based fault detection of wind turbinesYu, SongyangZhang, Yang2018With the development of renewable energy, the wind-energy generation is no longer a brand-new field. Considering the complex work environment and huge maintenance fee, windmill detection plays a significant role in the wind industry. Therefore, combining with the application of digital image technology in windmill in recent years, the thesis proposes a new non-destructive detection method based on digital image process algorithms, including Optical Intensity for frequency and cycle time measurement, Frame Difference for motion tracking, and EVM (Eulerian Video Magnification) for invisible motion enhancement.621University of Sheffieldhttps://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755167http://etheses.whiterose.ac.uk/19722/Electronic Thesis or Dissertation
collection	NDLTD
sources	NDLTD
topic	621
spellingShingle	621 Yu, Songyang Imaging-based fault detection of wind turbines
description	With the development of renewable energy, the wind-energy generation is no longer a brand-new field. Considering the complex work environment and huge maintenance fee, windmill detection plays a significant role in the wind industry. Therefore, combining with the application of digital image technology in windmill in recent years, the thesis proposes a new non-destructive detection method based on digital image process algorithms, including Optical Intensity for frequency and cycle time measurement, Frame Difference for motion tracking, and EVM (Eulerian Video Magnification) for invisible motion enhancement.
author2	Zhang, Yang
author_facet	Zhang, Yang Yu, Songyang
author	Yu, Songyang
author_sort	Yu, Songyang
title	Imaging-based fault detection of wind turbines
title_short	Imaging-based fault detection of wind turbines
title_full	Imaging-based fault detection of wind turbines
title_fullStr	Imaging-based fault detection of wind turbines
title_full_unstemmed	Imaging-based fault detection of wind turbines
title_sort	imaging-based fault detection of wind turbines
publisher	University of Sheffield
publishDate	2018
url	https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.755167
work_keys_str_mv	AT yusongyang imagingbasedfaultdetectionofwindturbines
_version_	1718996016635576320

Imaging-based fault detection of wind turbines

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