摘要
为提高露天矿山自动管理能力,促进矿山生产安全高质量发展,利用深度学习和视频分析技术构建露天矿山生产安全监测系统。首先,设计矿山人工智能中台,统一管理适用于不同矿山作业场景的深度学习应用;其次,设计矿山实时视频分析推理告警机制,分析AI中台识别到的各种作业场景在时间和空间维度上是否合规,对违规场景进行告警;最后,告警机制联合控制摄像云台,对违规场景进行录像。结果表明:该系统对矿山作业现场实时视频流的分析速度达16.7 ms/帧,对违规场景的检出率92.3%,误检率3.6%,提高了露天矿山生产安全水平,为露天矿山的安全生产提供了良好的参考价值。
In order to improve the automatic management capability of open-pit and promote the highquality development of open-pit production safety,an open-pit production safety monitoring system was developed using deep learning and video analytics.Firstly,an open-pit artificial intelligence(AI)midplatform was designed to manage deep learning applications of different open-pit working scenes.Secondly,an analysis and inference alarm mechanism was designed using open-pit real-time video to analyze whether the various working scenes identified by the AI mid-platform are compliant in timespace relation,and alarm the non-compliant scenes.Finally,non-compliant scenes will be recorded by the PTZ camera under control of the alarm mechanism.The results show that the system can analyze the real-time video stream of open-pit work scenes at a speed of 16.7 milliseconds per frame,with the detection rate of 92.3%and the missing rate of 3.6%for non-compliant scenes,improve the open-pit production safety level,and provide reference value for the production safety of open-pit.
作者
王国昌
潘冰冰
李琦
WANG Guochang;PAN Bingbing;LI Qi(School of Information Engineering,Inner Mongolia University of Science and Technology,Baotou 014017,China)
出处
《煤炭技术》
CAS
北大核心
2023年第11期162-166,共5页
Coal Technology
基金
内蒙古关键技术攻关项目(2020GG0316)
内蒙古自然基金资助项目(2020MS06008)。
关键词
生产安全
深度学习
视频分析
露天矿山
人工智能中台
云台控制
production safety
deep learning
video analytics
open-pit
artificial intelligence(AI)midplatform
PTZ control