中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

Journal of Chongqing Jiaotong University(Natural Science) ›› 2014, Vol. 33 ›› Issue (2): 5-9.DOI: 10.3969/j.issn.1674-0696.2014.02.02

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Development of Cable Inspection System ?ased on Image Processing

Liu Chaotao1, Du Zixue1, Wu Wei1, Xiang Zhongfu2   

  1. 1. Schoo1 of Mechatronics & Automotive Engineering , Chongqing Jiaotong University , Chongqing 400074 , China; 2. School of Civil Engineering & Architecture , Chongqing Jiaotong University , Chongqing 400074 , China
  • Received:2012-11-21 Revised:2013-03-10 Online:2014-04-15 Published:2015-01-22

基于图像处理的桥梁缆索检测系统研制

刘朝涛1,杜子学1,武维1,向中富2   

  1. 1. 重庆交通大学 机电与汽车工程学院,重庆 400074;2 重庆交通大学 土木建筑学院,重庆 400074
  • 作者简介:刘朝涛(1968-) ,男,四川岳池人,副教授,博士.主要从事智能控制,机电一体化系统方面的研究。E-mail: liuchaotao@163.com

Abstract: A stayed cable health inspection system based on the image acquisition and processing was developed , which con sisted of robot , hosl computer , cameras and image acquisition syslem. The robot was driven with single motor and could automatically climb cables of various diameters. Omni-directional pictures of the cables were taken by the robot , and the de fects and mars were identified through the automatical recognition of the cable image. The steps of image recognition including image de-noising , image enhancement , image segmentation and feature extraclion , and lhe defecls and mars were iden tified from the features of the grayscale distributions and energy distributions in grey level histogram.

Key words: bridge engineering, cable inspection, image, hislogram, defecl recognition

摘要: 研制了一套基于图像采集和处理的桥梁缆索健康检测系统,包括检测机器人、上位计算机、相机及图像采集系 统。检测机器人采用单电机驱动,能自动适应不同直径的缆索。机器人通过对缆索进行全方位照相,并对缆索图像 进行自动识另1],来判断缆索的病害。对采集的缆索罔像,经过图像去躁、图像增强、罔像分割、特征提取,最后以用像 的灰度直方图中的灰度分布和能量分布等为特征进行病害识别。

关键词: 桥梁工程, 缆索检测, 图像, 直方图, 病害识别

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