船舶机舱危险行为智能视觉监控系统
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  • 英文篇名:Intelligent visual monitoring system for dangerous behavior of marine engine room
  • 作者:李淑娟
  • 英文作者:LI Shu-juan;Department of Computer and Information Technology, Zhejiang Changzheng Vocational and Technical College;
  • 关键词:危险行为 ; 视觉监控 ; ZigBee框架 ; 复位电路
  • 英文关键词:dangerous behavior;;visual monitoring;;ZigBee framework;;reset circui
  • 中文刊名:JCKX
  • 英文刊名:Ship Science and Technology
  • 机构:浙江长征职业技术学院计算机与信息技术系;
  • 出版日期:2019-06-23
  • 出版单位:舰船科学技术
  • 年:2019
  • 期:v.41
  • 语种:中文;
  • 页:JCKX201912062
  • 页数:3
  • CN:12
  • ISSN:11-1885/U
  • 分类号:185-187
摘要
为实现对船舶舱室的智能化管理,设计船舶机舱危险行为的智能视觉监控系统。在ZigBee监控框架中,按需连接智能复位电路和视觉服务器,完成监控系统的硬件运行环境搭建。根据Linux监控内核的移植标准,连接视觉服务器获取的监控数据,完成监控系统的软件运行环境搭建,结合所有硬件执行设备,实现船舶机舱危险行为智能视觉监控系统的顺利应用。对比实验结果表明,在特定指标环境下,应用智能视觉监控系统可在最短时间发现船舶机舱内的危险行为,并对其进行精准的定位监控,有效解决现有技术手段在船舶舱体智能化管理方面存在的问题。
        In order to realize intelligent management of ship cabin, an intelligent visual monitoring system for dangerous behavior of ship engine room is designed. In the ZigBee monitoring framework, the intelligent reset circuit and visual server are connected on demand to complete the hardware environment of the monitoring system. According to the transplantation standard of Linux monitoring kernel, the monitoring data acquired by visual server is connected, the software running environment of the monitoring system is built, and the intelligent visual monitoring system for dangerous behavior of ship engine room is successfully applied with all hardware executing devices. The comparative experimental results show that the application of intelligent visual surveillance system can detect the dangerous behavior in the engine room in the shortest time under the specific index environment, and carry out accurate positioning and monitoring, effectively solve the existing technical means in the intelligent management of the ship cabin.
引文
[1]董亚力,王丹,秦荣明.基于智能视觉的近海支持船靠泊作业安全监控技术[J].现代电子技术,2017,40(24):88-90.
    [2]万琴,余洪山,吴迪,等.基于三维视觉系统的多运动目标跟踪方法综述[J].计算机工程与应用,2017,53(19):33-39.4.
    [3]赵春宇.基于CAN总线的船舶机舱危险行为智能视觉监控系统[J].舰船科学技术,2018,40(18):118-120.

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