|本期目录/Table of Contents|

[1]蔡晨晖,梁晓刚,师剑雄,等.矿山视频大数据智能分析与安全生产监控平台研究*[J].中国安全生产科学技术,2024,20(1):65-70.[doi:10.11731/j.issn.1673-193x.2024.01.010]
　CAI Chenhui,LIANG Xiaogang,SHI Jianxiong,et al.Research on mine video big data intelligent analysis and work safety monitoring platform[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2024,20(1):65-70.[doi:10.11731/j.issn.1673-193x.2024.01.010]
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矿山视频大数据智能分析与安全生产监控平台研究*
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
20
期数:
2024年1期
页码:
65-70
栏目:
职业安全卫生管理与技术
出版日期:
2024-01-31

文章信息/Info

Title:
Research on mine video big data intelligent analysis and work safety monitoring platform
文章编号:
1673-193X(2024)-01-0065-06
作者:
蔡晨晖; 梁晓刚; 师剑雄; 白艳
(1.甘肃建投绿色建材产业发展集团有限公司，甘肃 兰州 730000；
2.中国科学院地理科学与资源研究所，北京 100101)
Author(s):
CAI Chenhui;  LIANG Xiaogang;  SHI Jianxiong;  BAI Yan
(1.Gansu Jiantou Green Building Materials Industry Development Group,Lanzhou Gansu 730000,China;
2.Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China)
关键词:
目标检测; 矿山安全监管; YOLOv5; 三维可视化; 监控系统
Keywords:
object detection;  mining safety supervision;  YOLOv5;  3D visualization;  monitoring system
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2024.01.010
文献标志码:
A
摘要:
为了实现对现代化大型矿山生产的全时段、全过程、全域覆盖的安全监测与监管，提出集成地理信息技术、5G技术、三维矿区及装备模型、遥感与视频监测、人工智能等多项信息技术的整体技术方案，并协同设计智慧矿山安全生产监控系统平台。研究结果表明：基于视频大数据智能分析技术，遴选视频目标自动检测算法，集成对YOLOv5算法进行Mosaic-9数据增强、K-means聚类先验锚框与损失函数优化等改进技术，可实现现实场景中安全帽佩戴、反光衣穿戴以及烟雾火灾等视频自动化识别监测功能与虚拟三维模型的可视化融合，可为实现矿山安全全天候智能化、可视化监管提供分析平台。
Abstract:
In order to realize the safety monitoring and supervision of modern large-scale mining production with whole time,whole process,and whole area coverage,an overall technical scheme integrating the geographic information technology,5G technology,3D mining area and equipment model,remote sensing and video monitoring,artificial intelligence and other information technologies was proposed,and the intelligent mine work safety monitoring system platform was designed collaboratively.The results show that based on the video big data intelligent analysis technology,the automatic detection algorithm of video target is selected,and the Mosaic-9 data augmentation,K-means clustering prior anchor box and loss function optimization of YOLOv5 algorithm are integrated,so as to realize the visual integration of video automatic recognition and monitoring functions such as helmet wearing,reflective clothing wearing and smoke fire in real scenes with virtual three-dimensional models,which can provide an analysis platform for realizing the all-weather intelligent visual supervision of mine safety.

参考文献/References:

［1］王启明.非煤矿山安全生产形势、问题及对策［J］.金属矿山,2005（10）:1-6. WANG Qiming.Situation of safety production in non-coal mines and its problems and countermeasures［J］.Metal Mine,2005（10）:1-6.
［2］王成,孙宝生,张建,等.中国矿山安全现状与对策［J］.矿业研究与开发,2006,26(2):81-85. WANG Cheng,SUN Baosheng,ZHANG Jian,et al.On the current situation and countermeasures of mine safety in China［J］.Mining Research and Development,2006,26(2):81-85.
［3］吴立新,汪云甲,丁恩杰,等.三论数字矿山-借力物联网保障矿山安全与智能采矿［J］.煤炭学报,2012,37(3):357-365. WU Lixin,WANG Yunjia,DING Enjie,et al.Thirdly study on digital mine:serve for mine safety and intellimine with support from loT［J］.Journal of China Coal Society,2012,37(3):357-365.
［4］程桂花,沈炜,何松林,等.Node.js中Express框架路由机制的研究［J］.工业控制计算机,2016，29(8):101-102. CHENG Guihua,SHEN Wei,HE Songlin,et al.Study of express framework’s routing mechanism in Node.js［J］.Industrial Control Computer,2016,29(8):101-102.
［5］余小高.用OO4O和VC++开发ORACLE数据库应用程序的方法研究［J］.交通与计算机,2003（1）:78-80. YU Xiaogao.Research on developing ORACLE database application with OO4O and VC++［J］.Journal of Transport Information and Safety,2003（1）:78-80.
［6］张珈睿.深度学习在目标检测技术优化中的应用［J］.电子技术.2023,52(1):348-349. ZHANG Jiarui.Application of deep learning in target detection technology optimization［J］.Electronic Technology,2023,52(1):348-349.
［7］ZHAO Z Q,ZHENG P,XU S T,et al.Object detection with deep learning:A review［J］.IEEE Transactions on Neural Networks and Learning Systems,2019,30(11):3212-3232.
［8］XU Z,LI J Z,ZHANG M.A surveillance video real-time analysis system based on edge-cloud and FL-YOLO cooperation in coal mine［J］.IEEE Access,2021（9）:68482-68497.
［9］AJIT A,ACHARYA K,SAMANTA A.A review of convolutional neural networks［C］//2020 International Conference on Emerging Trends in Information Technology and Engineering,Vellore,India,2020:1-5.
［10］ALBAWI S,MOHAMMED T A,AL-ZAWI S.Understanding of a convolutional neural network［C］//2017 International Conference on Engineering and Technology (ICET),Antalya,Turkey,2017:1-6.
［11］HUANG L,LI J,HAO H,et al.Micro-seismic event detection and location in underground mines by using Convolutional Neural Networks (CNN) and deep learning［J］.Tunnelling and Underground Space Technology,2018,81:265-276.
［12］李梅,姜展,姜龙飞,等.三维可视化技术在智慧矿山领域的研究进展［J］.煤炭科学技术.2021,49(2):153-162. LI Mei,JIANG Zhan,JIANG Longfei,et al.Research progress on 3D visualization technology for intelligent mine［J］.Coal Science and Technology,2021,49(2):153-162.
［13］WALLER J,WULF C,FITTKAU F,et al.Synchrovis:3D visualization of monitoring traces in the city metaphor for analyzing concurrency［C］//2013 First IEEE Working Conference on Software Visualization (VISSOFT),Eindhoven,Netherlands,2013:1-4.
［14］CHAI J F,HU X M,QU H W,et al.Production line 3D visualization monitoring system design based on OpenGL［J］.Advances in Manufacturing,2018,6（1）:126-135.
［15］朱周华,齐琦.基于改进YOLOv5s电动车头盔的自动检测与识别［J］.计算机应用,2023,43(4):1291-1296. ZHU Zhouhua,QI Qi.Automatic detection and recognition of electric vehicle helmet based on improved YOLOv5s［J］.Coal Science and Technology,2023,43(4):1291-1296.
［16］肖粲俊,刘红梅,石发强等.基于数字孪生的煤矿智能管控平台架构研究与实现［J/OL］.矿业安全与环保:1-9［2023-10-26］.http://kns.cnki.net/kcms/detail/50.1062.TD.20230315.1847.005.html.
［17］毛乾宇.基于卫星遥感及GIS空天地一体化智慧矿山技术研究及应用［J］.煤炭科技,2023,44(3):172-176. MAO Qianyu.Research and application of intelligent mining technology based on satellite remote sensing and GlS for space sky integration［J］.Mining Safety and Environmental Protection,2023,44(3):172-176.
［18］沈铭华,马昆,杨洋,等.AI智能视频识别技术在煤矿智慧矿山中的应用［J］.煤炭工程,2023,55(4):92-97. SHEN Minghua,MA Kun,YANG Yang,et al.Application of AI identification technology in intelligent coal mine［J］.Coal Engineering,2023,55(4):92-97.
［19］TALPUR S H,CHOHAN A,MAHAR M A,et al.Smarthelmet for coal mines safety monitoring with mobile APP［J］.International Journal of Computational Intelligence in Control,2022,13(2):0974-8571.
［20］LAAYATI O,BOUZI M,CHEBAK A.Smartenergy management system:design of a monitoring and peak load forecasting system for an experimental open-pit mine［J］.Applied System Innovation,2022（5）:1-18.
［21］白莹.基于视频智能识别的带式运输机安全检测系统［J］.现代矿业,2023,39(6):59-62. BAI Ying.Safety detection system of belt conveyor based on video intelligent recognition［J］.Modern Mining,2023,39(6):59-62.
［22］张恒.小保当煤矿视频安防监控系统的设计［J］.煤炭技术,2023,42(5):241-244. ZHANG Heng.Design of video security monitoring system in Xiaobaodang mine［J］.Coal Technology,2023,42(5):241-244.
［23］陆世东,周洪文,颜宇,等.矿山视频三维监测软件系统研发［J］.能源与节能,2023（4）:95-98. Lu Shidong,ZHOU Hongwen,YAN Yu,et al.Research and development of mine video 3D monitoring software system［J］.Energy and Energy Conservation,2023（4）:95-98.
［24］牛鹏程.基于智慧矿山建设的煤矿智能化高效整合研究［J］.内蒙古煤炭经济,2022（24）:37-39. NIU Pengcheng.Research on intelligent and efficient integration of coal mine based on smart mine construction［J］.Inner Mongolia Coal Economy,2022（24）:37-39.
［25］田将杉.煤矿视频监控系统的应用现状与发展趋势［J］.机械管理开发,2017,32(9):130-131. TIAN Jiangshan.Status and development trend of video monitoring system in coal mine machinery［J］.Mechanical Management and Development,2017,32(9):130-131.

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备注/Memo

备注/Memo:
收稿日期： 2023-07-12
* 基金项目： 兰州市科技计划项目(2021-1-20);甘肃省科技计划项目(22CX8JA144)
作者简介： 蔡晨晖，本科，工程师，主要研究方向为绿色智慧矿山建设及矿山安全管理。
通信作者： 白艳，硕士研究生，工程师，主要研究方向为绿色智慧矿山建设及矿山安全管理。
更新日期/Last Update: 2024-02-19