中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (S2): 118-122.doi: 10.16265/j.cnki.issn1003-3033.2022.S2.0176

• 安全工程技术 • 上一篇    下一篇

基于物联网的职业健康监测预警体系研究与应用

李光华(), 蒋杨, 王朝盆   

  1. 国家能源集团 大渡河大岗山发电有限公司, 四川 雅安 625400
  • 收稿日期:2022-08-30 修回日期:2022-10-25 出版日期:2022-12-30 发布日期:2023-06-30
  • 作者简介:

    李光华 (1985—),男,河南商丘人,硕士,工程师,主要从事水电站运维管理、智能安全风险管控、水电站数字化改造以及智能化应用方面的工作。E-mail:

Research and application of occupational health monitoring and warning system based on Internet of things

LI Guanghua(), JIANG Yang, WANG Chaopen   

  1. Dadu River Dagangshan Power Generation Co., Ltd., CHN Energy, Ya'an Sichuan 625400, China
  • Received:2022-08-30 Revised:2022-10-25 Online:2022-12-30 Published:2023-06-30

摘要:

为实时监测预警水电站生产现场职业病危害因素,保障水电站从业人员的职业健康安全。某水电站依托大数据、云计算、人工智能、互联网和物联网等技术,以地下洞室厂房环境中有毒有害气体、噪声及电磁辐射等水电站职业健康安全危害因素为研究对象,设计研发具备职业病危害因素实时防控功能的软硬件系统,构建职业健康智能监测预警体系。结果表明:该预警体系统筹水电行业职业健康信息化基础设施建设、应用系统和网络安全配置,依据职业病危害因素防治标准,在地下洞室群全方位部署职业病危害因素实时感知及监测仪器,构建职业病危害因素超标风险预警算法模型,对有毒有害气体、噪声、电磁辐射等水电站职业病危害因素动态、实时地监测、综合分析预警。职业健康监测预警体系的建成和投运消除传统人工定期检测的缺陷,实现对职业危害因素全面、长期地控制和防范。

关键词: 物联网, 职业健康, 监测预警体系, 危害因素, 协同联动

Abstract:

In order to monitor and warn the occupational hazard factors at the production site in real time and ensure the occupational health and safety of the employees, a hydropower station took occupational health and safety hazard factors in underground chambers and workshops as research objects. These factors included toxic and harmful gas, noise, and electromagnetic radiation. In addition, the station used big data, cloud computing, artificial intelligence, Internet, Internet of things, and other technologies to design and develop a software and hardware system. The system could prevent and control occupational hazard factors in real time. The station also built an intelligent occupational health monitoring and warning system. The results show that the construction of occupational health information infrastructure, application system, and network security configuration in the hydropower industry are coordinated by the warning system. Real-time perception and monitoring devices for occupational hazard factors in underground caves are comprehensively deployed according to the prevention and control standard of occupational hazard factors. In addition, a risk warning algorithm model for occupational hazard factors exceeding the standard is constructed. On the one hand, the model can dynamically monitor occupational hazard factors, such as toxic and harmful gas, noise, and electromagnetic radiation in real time. On the other hand, it can ensure comprehensive analysis and early warning. The occupational health monitoring and warning system is established and implemented. As a result, the system eliminates the defects of traditional manual periodic detection and realizes the comprehensive and long-term control and prevention of occupational hazard factors.

Key words: Internet of things, occupational health, monitoring and warning system, hazard factors, linkage