On-line conveyor belts inspection based on machine vision

被引：99

作者：

Yang, Yanli ^{[1
]}

Miao, Changyun ^{[1
]}

Li, Xianguo ^{[1
]}

Mei, Xiuzhuang ^{[1
]}

机构：

[1] Tianjin Polytech Univ, Sch Elect & Informat Engn, Tianjin 300387, Peoples R China

来源：

OPTIK | 2014年 / 125卷 / 19期

基金：

中国国家自然科学基金;

关键词：

Machine vision; CCD camera; Conveyor belt; Longitudinal rip; Ethernet; SYSTEM;

D O I：

10.1016/j.ijleo.2014.07.070

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Under the background that mining conveyor belts are prone to failure in operation, the on-line fault detection technique based on machine vision for conveyor belts is investigated. High-brightness linear light sources arranged to a vaulted shape provide light for a line-array CCD camera to capture high-quality belt images. A fast image segmentation algorithm is proposed to deal belt images on-line. The algorithm for detecting longitudinal rip and belt deviation which are serious threat to the mine safety production from binary belt images is presented. Then, an on-line visual belt inspection system is developed. The laboratory testing results testify the validity of the visual inspection system. (C) 2014 Elsevier GmbH. All rights reserved.

引用

页码：5803 / 5807

页数：5

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