Study on monitoring method of wind power blades erosion severity under wind-sand storm based on machine vision technology

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	Study on monitoring method of wind power blades erosion severity under wind-sand storm based on machine vision technology
	Wang, Xueping1,2,3 ; Zhang, Jianfei 1; Li, Wanrun1,2,3 ; Du, Yongfeng1,2,3 ; Li, Hui 1,2,3
	2020-05-28
发表期刊	Taiyangneng Xuebao/Acta Energiae Solaris Sinica
ISSN	02540096
卷号	41 期号:5 页码:166-173
摘要	The generating efficiency of wind power and safety of wind power structure are seriously influenced by such defects as eroded pits, scratches, cracks, etc. caused from surface of wind power blades under wind sand environment. A kind of nondestructive detecting method for the surface of wind power blades based on machine vision is put forward in this thesis to rapidly detect out whether there is defect on the surface of blades. The method combines machine vision theory and image processing techniques to realize the identification of defect area in blade and extraction of characteristic parameters by such algorithms as graying, spatial filtering, image intensification, image segmentation, image denoising, morphological remodeling, etc. For collected blade images, so as to reduce the impact of noise and artificial reading on defect accuracy of blade surface, for providing reference for the automation and digitization of future nondestructive detection. © 2020, Editorial Board of Acta Energiae Solaris Sinica. All right reserved.
关键词	Computer vision Image segmentation Wind power Extraction of characteristics Generating efficiencies Image intensification Image processing technique Monitoring methods Nondestructive detecting method Nondestructive detection Spatial filterings
收录类别	EI
语种	中文
出版者	Science Press
EI入藏号	20202508857775
EI主题词	Image denoising
EI分类号	615.8 Wind Power (Before 1993, use code 611 ) ; 716.1 Information Theory and Signal Processing ; 723.5 Computer Applications
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/150804
专题	土木工程学院基建规划处
作者单位	1.Earthquake Protection and Disaster Mitigation Institute, Lanzhou University of Technology, Lanzhou; 730050, China; 2.School of Civil Engineering, Lanzhou University of Technology, Lanzhou; 730050, China; 3.Disaster Prevention and Mitigation Engineering Research Center of Western Civil Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
第一作者单位	兰州理工大学; 土木工程学院
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Wang, Xueping,Zhang, Jianfei,Li, Wanrun,et al. Study on monitoring method of wind power blades erosion severity under wind-sand storm based on machine vision technology[J]. Taiyangneng Xuebao/Acta Energiae Solaris Sinica,2020,41(5):166-173.
APA	Wang, Xueping,Zhang, Jianfei,Li, Wanrun,Du, Yongfeng,&Li, Hui.(2020).Study on monitoring method of wind power blades erosion severity under wind-sand storm based on machine vision technology.Taiyangneng Xuebao/Acta Energiae Solaris Sinica,41(5),166-173.
MLA	Wang, Xueping,et al."Study on monitoring method of wind power blades erosion severity under wind-sand storm based on machine vision technology".Taiyangneng Xuebao/Acta Energiae Solaris Sinica 41.5(2020):166-173.