Research on visible light and infrared vision real-time detection system for conveyor belt longitudinal tear

被引:21
作者
Qiao, Tiezhu [1 ]
Liu, Weili [1 ]
Pang, Yusong [2 ]
Yan, Gaowei [3 ]
机构
[1] Taiyuan Univ Technol, Minist Educ & Shanxi Prov, Key Lab Adv Transducers & Intelligent Control Sys, Taiyuan 030024, Peoples R China
[2] Delft Univ Technol, Fac Mech, Sect Transport Engn & Logist, NL-2628 CD Delft, Netherlands
[3] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Peoples R China
基金
中国国家自然科学基金;
关键词
optical sensors; CCD image sensors; conveyors; belts; infrared detectors; Hough transforms; life testing; infrared vision real-time detection system; visible light real-time detection system; conveyor belt longitudinal tear; coal mining; length detection; longitudinal tear detection; visible light charge coupled device; infrared CCD; adaptive histogram equalisation; Hough transform line detection algorithm; laser line source; accelerated segment test algorithm; MONITORING-SYSTEM; RECOGNITION; FIRE;
D O I
10.1049/iet-smt.2015.0297
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Conveyor belt longitudinal tear is one of the most serious problems in coal mining. It is very important to detect it in real-time before the length of the tear is too long. In this study, a method of longitudinal tear detection based on visible light charge coupled device (CCD) and infrared CCD is proposed. A visible light and infrared vision real-time detection system for conveyor belt longitudinal tear is designed based on this method. In this method, the infrared CCD uses adaptive histogram equalisation coordinating with Hough transform line detection. The visible light CCD, coordinating with a laser line source, uses the Hough transform algorithm and the features from accelerated segment test algorithm. These two kinds of CCDs work together to make detection results reliable. Experimental results show that the proposed method is effective and adaptive, and meets the requirements for reliable, real-time and online longitudinal tear detection. Compared to several current methods, the proposed method has a better performance on efficiency of detection.
引用
收藏
页码:577 / 584
页数:8
相关论文
共 20 条
  • [1] [Anonymous], 2013, Learning OpenCV: Computer Vision in C++ with the OpenCVLibrary
  • [2] Probing Planck's law at home
    Bonnet, I.
    Gabelli, J.
    [J]. EUROPEAN JOURNAL OF PHYSICS, 2010, 31 (06) : 1463 - 1471
  • [3] Automatic number plate information extraction and recognition for intelligent transportation system
    Cinsdikici, Muhammed
    Ugur, Aybars
    Tunali, Turhan
    [J]. IMAGING SCIENCE JOURNAL, 2007, 55 (02) : 102 - 113
  • [4] Di S., 2014, THESIS
  • [5] Fromme C., 2006, US Patent, Patent No. [6,988,610, 6988610]
  • [6] MONITORING-SYSTEM FOR STEEL-REINFORCED CONVEYOR BELTS
    HARRISON, A
    BROWN, BC
    [J]. JOURNAL OF ENGINEERING FOR INDUSTRY-TRANSACTIONS OF THE ASME, 1986, 108 (02): : 148 - 153
  • [7] Hough PVC, 1962, U.S. Patent, Patent No. 3069654
  • [8] Fire detection - A new approach based on a low cost CCD camera in the near infrared
    Le Maoult, Y.
    Sentenac, T.
    Orteu, J. J.
    Arcens, J. P.
    [J]. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2007, 85 (B3) : 193 - 206
  • [9] Multiframe-Based High Dynamic Range Monocular Vision System for Advanced Driver Assistance Systems
    Li, You
    Qiao, Yongliang
    Ruichek, Yassine
    [J]. IEEE SENSORS JOURNAL, 2015, 15 (10) : 5433 - 5441
  • [10] LIDONG H, 2015, IET IMAGE PROCESS, V9, P908, DOI DOI 10.1049/IET-IPR.2015.0150