摘要
针对石油企业现有生产安全预警系统存在安全管理不全面、系统实时性和联动性差等问题。提出下一代的生产安全智能预警系统运用大数据、物联网和人工智能等技术实时采集人、物、环境数据并和安全管理结合在一起,实现精准安全管理。生产安全智能预警系统层次包括感知层、网络层、数据层、服务层、应用层,可以实现安全数据全面收集与处理,对人的不安全行为、物的不安全状态、环境不良进行监控报警,并通过建立的安全模型进行分析与预测,系统为从源头做好安全管理提供支撑。
In view of the problems of incomplete safety management,poor system real-time and linkage in the existing production safety early warning system of oil enterprises,it is proposed to use big data,Internet of Things and artificial intelligence to collect real-time human,object and environmental data and combine it with safety management.Together,we can achieve the goal of precise security monitoring.The layers of the production safety intelligent early warning system include the perception layer,the network layer,the data layer,the service layer,and the application layer,which can realize the comprehensive collection and processing of safety data,and monitor and alarm the unsafe behavior of people,the unsafe state of things,and the bad environment.Analyze and predict through the established security model.Provide support for safety management from the source.
作者
王刚
彭远春
金雪梅
廖浩
Wang Gang;Peng Yuangchun;Jing Xuemei;Lao Hao(China National Petroleum Corporation Chuanqing Drilling Engineering Co.,Ltd.Safety and Environmental Quality Supervision and Inspection Institute,Guanghan Sichuan 618300)
出处
《石化技术》
CAS
2022年第10期72-74,共3页
Petrochemical Industry Technology
基金
国家重大科技专项(No.2016ZX05020-006)资助。
关键词
大数据
人工智能
预警系统
生产安全
Big data
Artificial intelligence(ai)
Early warning system
Production safety
作者简介
王刚,(1970-),男,毕业于西南科技大学,现任安全环保质量监督检测研究院工程师,主要从事安全管理工作。
