[1]赵春溢,郭洪涛,郭 涛,等. 一种风机叶片图像采集及缺陷检测系统[J].红外技术,2020,42(12):1203-1210.[doi:10.11846/j.issn.1001_8891.202012012]
 ZHAO Chunyi,GUO Hongtao,GUO Tao,et al.Defect Detection System Based on UAV Images for Wind Turbine Blades[J].Infrared Technology,2020,42(12):1203-1210.[doi:10.11846/j.issn.1001_8891.202012012]
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 一种风机叶片图像采集及缺陷检测系统
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
42卷
期数:
2020年第12期
页码:
1203-1210
栏目:
出版日期:
2020-12-22

文章信息/Info

Title:
Defect Detection System Based on UAV Images for Wind Turbine Blades
文章编号:
1001-8891(2020)10-1203-08
作者:
赵春溢郭洪涛郭 涛梁 国荆海城
中电投东北新能源发展有限公司,辽宁 沈阳 110179
Author(s):
ZHAO ChunyiGUO HongtaoGUO TaoLIANG GuoJING Haicheng
SPIC Northeast New Energy Development Co., Ltd., Shenyang 110000, China
关键词:
无人机风机叶片缺陷检测图像处理
Keywords:
UAV wind turbine blade defect defection image processing
分类号:
TP391
DOI:
10.11846/j.issn.1001_8891.202012012
文献标志码:
A
摘要:
本文针对目前风机叶片人工检测工作量大、效率低、缺陷检测准确率不高的问题,提出并设计了一种基于无人机图像的缺陷自动化检测系统。本文介绍了系统的图像采集系统、采集方法、缺陷检测原理及检测效果:系统以无人机为飞行载体实现了(风机叶片的)自动巡检,从而提高了巡检效率,降低了人工的工作量;通过图像分割及缺陷检测算法设计实现了缺陷可疑区域的自动检测;可见光加红外光双光融合提高了叶片缺陷自动识别的准确性。经过多次现场测试验证,本系统可以精确、快速地实现鼓包,裂纹和褶皱等缺陷的自动识别与检测。
Abstract:
This study proposes and designs an automatic defect detection system based on UAV images for wind turbine blades, aimed at alleviating problems with manual detection methods, such as low efficiency and inaccurate defect detection. This paper introduces the system’s image acquisition system, acquisition method, defect detection principle, and detection result. This system uses a UAV as the flying carrier to realize automatic inspection of wind turbine blades, thereby improving the inspection efficiency and reducing the manual workload. Through image segmentation and defect detection algorithm design, automatic detection of suspicious defect areas is achieved. Double light fusion of visible and infrared light improves the accuracy of automatic blade defect recognition. After multiple field tests and verification, the system is shown to accurately and quickly realize the automatic identification and detection of defects, such as bulges, cracks, and wrinkles.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2020-04-04;修订日期:2020-05-18.
作者简介:赵春溢(1970-),男,学士学位,高级工程师,主要研究方向火电及新能源技术管理,E-mail:sshsdsfyj@126.com。
通信作者:荆海城(1973-),男,学士学位,高级工程师,主要研究方向为新能源技术管理。E-mail:smart_3d@126.com。
更新日期/Last Update: 2020-12-21