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

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

1.
中国矿业大学信息与控制工程学院，江苏徐州　221116
2.
中国矿业大学计算机科学与技术学院，江苏徐州　221116

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
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- 文章访问数: 450
- HTML全文浏览量: 64
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- 被引次数: 0
出版历程
- 收稿日期: 2023-08-16
- 修回日期: 2023-11-10
- 网络出版日期: 2023-11-23

Overview of key technologies for mine-wide intelligent video analysis

1.
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
2.
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China

摘要

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。
- 煤矿智能化 /
- 智能视频分析 /
- AI视觉 /
- 视频采集与处理 /
- 视频识别与分析 /
- 视频监控预警
Abstract: Intelligence is the direction of coal mine development, and intelligent video analysis is an effective way to promote coal mine intelligence. The mine-wide intelligent video analysis technology has real-time monitoring, early warning, and decision support capabilities. It helps to improve the safety, production efficiency, resource utilization efficiency, and environmental sustainability of mining enterprises. The key technologies of mine-wide intelligent video analysis are introduced in detail, including video acquisition and processing technologies such as video acquisition equipment, video pre-processing, video compression and coding, basic video analysis technologies such as object detection and tracking, motion detection and analysis, object recognition and classification, and advanced video analysis technologies such as behaviour recognition and analysis, event detection and alarm, video monitoring and arming. A mining intelligent AI visual intelligence service platform that integrates video recognition analysis and industrial linkage control functions is developed. The paper introduces the application of intelligent video analysis technology in mining production scenarios such as intelligent water and gas exploration and discharge systems, coal rock recognition and cutting systems, heading working faces, fully mechanized working faces, coal flow transportation systems, mine hoist systems, auxiliary transportation systems, coal preparation plants, and intelligent loading and coal blending systems. The analysis points out that the current mine-wide intelligent video analysis technology still faces challenges in terms of video quality, complex backgrounds, real-time requirements, data privacy and security, system reliability and stability, etc. It is suggested to strengthen the research on algorithm improvement and optimization, multimodal data fusion, real-time analysis and edge computing, enhanced learning and independent decision-making, data privacy and security protection, hardware equipment and sensor technology in the future. Therefore, the development of mine-wide intelligent video analysis technology is comprehensively promoted and promote the process of mine intelligence is promoted.
- coal mine intelligence /
- intelligent video analysis /
- AI vision /
- video acquisition and processing /
- video recognition and analysis /
- video surveillance warning
注释:

1) 【编者按】全矿井智能视频分析技术是保障我国煤矿智能化建设和煤炭工业高质量发展的核心技术支撑。在矿井受限空间中，巷道空间结构复杂、电磁环境干扰强、人造光源照明不均匀、采掘运工作面粉尘及水雾大等环境因素，导致图像的成像质量较差、场景的高清重建困难、目标检测与识别精度不高等问题，严重制约矿井AI视频识别系统的智能化、精准化应用。为推动人工智能和计算机视觉驱动的智能视频分析技术在煤矿安全生产中的应用，促进学术交流，《工矿自动化》编辑部特邀中国矿业大学程德强教授为客座主编，中国矿业大学陈伟教授、煤炭科学技术研究院有限公司孟庆勇研究员为客座副主编，于2023年第11期策划出版“全矿井智能视频分析技术”专刊。在专刊出版之际，衷心感谢各位专家学者为专刊撰稿！感谢中国矿业大学、中国矿业大学（北京）、西安科技大学、中煤科工集团常州研究院有限公司、煤炭科学技术研究院有限公司等单位给予专刊组织过程中的大力支持！

HTML全文

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

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图 2 打钻管理界面

Figure 2. Drilling management interface

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图 3 煤岩识别界面

Figure 3. Coal-rock recognition interface

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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

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图 5 掘进进度监测和安全预警界面

Figure 5. Tunneling monitoring and safety pre-alarming interface

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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

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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

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图 8 矿井提升机状态监测界面

Figure 8. Status monitoring interface of mine hoist

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图 9 架空乘人装置识别界面

Figure 9. Recognition interface of overhead passenger device

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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

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图 11 车辆识别和跟踪界面

Figure 11. Vehicle recognition and tracking interface

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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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