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作 者:武熠明 徐明智 幸贞雄 WU Yi-ming;XU Ming-zhi;XING Zhen-xiong(Guizhou Institute of Labor Protection Science and Technology,Zunyi 563000,China)
机构地区:[1]贵州省劳动保护科学技术研究院,贵州遵义563000
出 处:《应用化工》2022年第S02期308-311,共4页Applied Chemical Industry
基 金:贵州省科研机构创新能力建设专项资金(黔科合服企[2020]4014)。
摘 要:为解决加油站缺乏有效监测人员行为的技术手段这一问题,寻找高效的技术措施来替代传统的人工监管模式,在调研贵州省内中石油、中石化、中航油及部分民营加油站企业,查阅有关资料的基础上,分析了加油站员工主要的不安全行为风险。针对风险的特点提出了4种监测算法,并结合机器视觉技术的研究现状,设计了加油站员工不安全行为智能监测预警系统,并介绍了系统的算法实现、整体架构和主要功能,对推动加油站的安全管理信息化发展、提高安全管理工作效率具有重要意义。In order to looking for advanced technology to replace traditional manual supervision methods to improving the current situation that gas stations lack technical means to effectively monitor personnel behavior,through the investigation of PetroChina,Sinopec,China Aviation Oil and some private enterprises in Guizhou Province,consulted security management of gas station and computer technology and other related information,analyzed the risk of employees’unsafe behavior in gas station,put forward four intelligence algorithms for these risks and designed the intelligent monitoring and early warning system for unsafe behavior of gas station employees based on the research status of machine vision.The algorithm implementation mode and working principle of the system,overall architecture and the tasks undertaken at each layer,and main function of the system have be introduced in the third section of the article.It's very important for promoting the development of safety management informatization in gas stations and improve the efficiency of safety management.
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