Volume 49 Issue 11
Nov.  2023
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Article Navigation >  Journal of Mine Automation  > 2023  >  49(11): 22-38, 75
DU Yuxin, ZHANG He, WANG Shuchen, et al. Research status and development trend of visual processing technology for fully mechanized excavation systems[J]. Journal of Mine Automation，2023，49（11）：22-38, 75.  doi: 10.13272/j.issn.1671-251x.2023090042
Citation: DU Yuxin, ZHANG He, WANG Shuchen, et al. Research status and development trend of visual processing technology for fully mechanized excavation systems[J]. Journal of Mine Automation，2023，49（11）：22-38, 75.  doi: 10.13272/j.issn.1671-251x.2023090042
shu

Research status and development trend of visual processing technology for fully mechanized excavation systems

doi: 10.13272/j.issn.1671-251x.2023090042
  • 1.

    School of Electrical and Control Engineering, Xuzhou University of Technology, Xuzhou 221018, China

  • 2.

    Zhongwei (Jiangsu) Urban Construction Design Co., Ltd., Xuzhou 221003, China

  • Received Date: 2023-09-12
  • Rev Recd Date: 2023-11-05
    • Available Online: 2023-11-27
    Abstract
  • Machine vision technology has the advantages of non-contact measurement, large amount of information acquisition, and strong data processing capability. Applying it to fully mechanized excavation faces is of great significance for improving the efficiency of fully mechanized excavation work, ensuring the safety of personnel and equipment, and reducing accidents. This article summarizes the specific application and development of visual processing technology in coal mine fully mechanized excavation systems in recent years. Based on the task division of fully mechanized excavation working faces and combined with specific practical cases, this paper focuses on the analysis of the application of machine vision technology in visual inspection and positioning, safety monitoring and accident prevention, and equipment automation and intelligence. By analyzing the structures and detection principles of various visual detection systems in different application scenarios, the technical performance, workflow, and advantages and disadvantages of visual processing technology in the application of fully mechanized excavation face engineering are clarified. This study analyzes the challenges of visual technology in the application of fully mechanized excavation face, including environmental adaptability issues, narrow imaging field of view, and the need to improve the robustness and reliability of intelligent algorithms. It is pointed out that multi-sensor information fusion technology, equipment group cooperative control technology and digital twin-driven remote monitoring technology are the new directions that need to be focused on in the future development of the intelligent equipment system of coal mine based on machine vision.

     

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