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全矿井智能视频分析关键技术综述

程德强 寇旗旗 江鹤 徐飞翔 宋天舒 王晓艺 钱建生

程德强,寇旗旗,江鹤,等. 全矿井智能视频分析关键技术综述[J]. 工矿自动化,2023,49(11):1-21.  doi: 10.13272/j.issn.1671-251x.18165
引用本文: 程德强,寇旗旗,江鹤,等. 全矿井智能视频分析关键技术综述[J]. 工矿自动化,2023,49(11):1-21.  doi: 10.13272/j.issn.1671-251x.18165
CHENG Deqiang, KOU Qiqi, JIANG He, et al. Overview of key technologies for mine-wide intelligent video analysis[J]. Journal of Mine Automation,2023,49(11):1-21.  doi: 10.13272/j.issn.1671-251x.18165
Citation: CHENG Deqiang, KOU Qiqi, JIANG He, et al. Overview of key technologies for mine-wide intelligent video analysis[J]. Journal of Mine Automation,2023,49(11):1-21.  doi: 10.13272/j.issn.1671-251x.18165

全矿井智能视频分析关键技术综述

doi: 10.13272/j.issn.1671-251x.18165
基金项目: 国家重点研发计划项目(2018YFC0808302);国家自然科学基金资助项目(52204177,52304182)。
详细信息
    作者简介:

    程德强(1979—),男,河南洛阳人,教授,博士,研究方向为图像智能检测与模式识别、图像处理与视频编码,E-mail:chengdq@cumt.edu.cn

  • 中图分类号: TD67

Overview of key technologies for mine-wide intelligent video analysis

  • 摘要: 智能化是煤矿发展的方向,而智能视频分析是促进煤矿智能化的有效途径。全矿井智能视频分析技术具有实时监控、预警和决策支持能力,有助于提高矿山企业的安全性、生产效率、资源利用效率和环境可持续性。详细介绍了全矿井智能视频分析的关键技术,包括视频采集设备、视频预处理、视频压缩与编码等视频采集与处理技术,目标检测与跟踪、运动检测与分析、物体识别与分类等视频分析基础技术,行为识别与分析、事件检测与警报、视频监控与布防等高级视频分析技术。研发了集成视频识别分析和工业联动控制功能的矿山智脑AI视觉智能服务平台,介绍了智能视频分析技术在智能探放水系统和探放瓦斯系统、煤岩识别与截割系统、掘进工作面、综采工作面、煤流运输系统、矿井提升机系统、辅助运输系统、选煤厂、智能化装车配煤系统等矿井生产场景中的应用。分析指出目前全矿井智能视频分析技术在视频质量、复杂背景、实时性要求、数据隐私和安全、系统可靠性与稳定性等方面仍面临挑战。建议未来加强算法提升和优化、多模态数据融合、实时分析和边缘计算、强化学习和自主决策、数据隐私和安全保护、硬件设备和传感器技术等方面的研究,以全面推动全矿井智能视频分析技术的发展,促进矿山智能化进程。

     

  • 图  1  矿山智脑AI视觉智能服务平台

    Figure  1.  Intelligent service platform based on AI video of mine smart brain

    图  2  打钻管理界面

    Figure  2.  Drilling management interface

    图  3  煤岩识别界面

    Figure  3.  Coal-rock recognition interface

    图  4  钻场智能管理子系统识别界面

    Figure  4.  Recognition interface of intelligent drilling field management subsystem

    图  5  掘进进度监测和安全预警界面

    Figure  5.  Tunneling monitoring and safety pre-alarming interface

    图  6  综采工作面作业安全监测与预警界面

    Figure  6.  Safety monitoring and pre-alarming interface of fully mechanized working face

    图  7  煤流运输系统异常检测与预测维护界面

    Figure  7.  Abnormal detection and predictive maintenance interface of coal transport system

    图  8  矿井提升机状态监测界面

    Figure  8.  Status monitoring interface of mine hoist

    图  9  架空乘人装置识别界面

    Figure  9.  Recognition interface of overhead passenger device

    图  10  设备状态监测和故障诊断界面

    Figure  10.  Interface of device status monitoring and fault diagnosis

    图  11  车辆识别和跟踪界面

    Figure  11.  Vehicle recognition and tracking interface

    图  12  水泵房定期巡检任务监管界面

    Figure  12.  Supervision interface of regular inspection task in pump house

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  • 收稿日期:  2023-08-16
  • 修回日期:  2023-11-10
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