Volume 50 Issue 9
Sep.  2024
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Article Navigation >  Journal of Mine Automation  > 2024  >  50(9): 66-74
SHAN Pengfei, YANG Tong, SUN Haoqiang, et al. Research on the characteristics of the falling behavior of mixed coal and gangue[J]. Journal of Mine Automation，2024，50（9）：66-74.  doi: 10.13272/j.issn.1671-251x.2024070058
Citation: SHAN Pengfei, YANG Tong, SUN Haoqiang, et al. Research on the characteristics of the falling behavior of mixed coal and gangue[J]. Journal of Mine Automation，2024，50（9）：66-74.  doi: 10.13272/j.issn.1671-251x.2024070058
shu

Research on the characteristics of the falling behavior of mixed coal and gangue

doi: 10.13272/j.issn.1671-251x.2024070058
  • 1.

    College of Energy Engineering, Xi'an University of Science and Technology, Xi'an 710054, China

  • 2.

    Key Laboratory of Western Mine Exploitation and Hazard Prevention, Ministry of Education, Xi'an University of Science and Technology, Xi'an 710054, China

  • Received Date: 2024-07-16
  • Rev Recd Date: 2024-10-10
    • Available Online: 2024-10-18
    Abstract
  • Traditional studies on the dynamic characteristics of coal flow during the top coal caving process, based on image detection technology, have primarily focused on specific-stage image analysis, lacking a comprehensive analysis of dynamic characteristics across all stages. Existing research has rarely integrated the changes in the loose zone of the overlying strata with coal and gangue separation and coal flow characteristics during top coal caving, resulting in a lack of systematic and holistic analysis of the entire coal caving process. In response to these issues, this study systematically investigated coal flow dynamics, coal and gangue separation effectiveness, and the subsidence of the loose zone in the overlying strata during the top coal caving. First, this paper proposed a dynamic analysis method for the top coal caving process based on a dual optical flow network. The results indicated that the coal caving speed was not affected by the caving method and pattern, and that average detection accuracy increased with the number of caving openings, exhibiting a notably linear increase during the periodic caving stage. The release rate of top coal showed a positive correlation with average detection accuracy, validating the effectiveness of the method in the top coal caving process monitoring. Second, OpenCV technology was used to conduct experimental analysis on the subsidence area of the loose zone in the overlying strata. Results demonstrated that the subsidence area grew sharply during the initial caving stage and gradually stabilized over time. The dynamic changes in the subsidence area effectively indicated the progression of top coal release, enabling transparent monitoring of release process. Finally, based on data from weighing experiments, the relationships among caving amount, release rate, and gangue content were analyzed. Results showed that the amount of pure coal release was the highest in the initial caving stage and stabilized in the periodic caving stage, while gangue content decreased as the number of caving openings increased. These findings further reveal the influence of caving methods on coal and gangue separation and the release rate of top coal.

     

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