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基于尾矿库安全物联网决策支持系统研究
引用本文:姜洲1,2,陈学力3,方伟立1,吴贤国1,肖旭峰3,刘方求3. 基于尾矿库安全物联网决策支持系统研究[J]. 中国安全生产科学技术, 2016, 12(5): 120-126. DOI: 10.11731/j.issn.1673-193x.2016.05.021
作者姓名:姜洲1  2  陈学力3  方伟立1  吴贤国1  肖旭峰3  刘方求3
作者单位:(1.华中科技大学 土木工程与力学学院, 湖北 武汉 430074; 2. 湖南省安全生产监督管理局,湖南 长沙 410016;3.湖南黄金洞矿业有限责任公司,湖南 长沙 410016)
摘    要:
尾矿库安全管理是一项非常复杂的系统工程,针对湖南黄金集团高流坑尾矿库安全管理工作人工依赖性强、智能化程度低,灾情实时判断与预警控制决策效率低等不足特点,提出物联网技术,结合先进的数据感知技术,将数据采集、处理、分析及决策等环节进行一体化综合集成,研究设计尾矿库安全物联网决策支持系统。使尾矿库建设运营参与各方加强认知和揭示尾矿库安全灾变规律,为实现尾矿库安全管理智能预警决策提供有力的辅助支持。

关 键 词:尾矿库  物联网  安全监控  数据采集

Research on decision-making support system of tailing pond safety based on Internet of Things
JIANG Zhou1,2,CHEN Xueli3,FANG Weili1,WU Xiangu1,XIAO Xufeng3,LIU Fangqiu3. Research on decision-making support system of tailing pond safety based on Internet of Things[J]. Journal of Safety Science and Technology, 2016, 12(5): 120-126. DOI: 10.11731/j.issn.1673-193x.2016.05.021
Authors:JIANG Zhou1  2  CHEN Xueli3  FANG Weili1  WU Xiangu1  XIAO Xufeng3  LIU Fangqiu3
Affiliation:(1. School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan Hubei 430074, China;2. Administration of Hunan Work Safety, Changsha Hunan 410016, China;3. Huang Jin Dong Mining Industry Limited Company of Hunan, Changsha Hunan 410016, China)
Abstract:
The safety management of tailing pond is a complicated system engineering. Aiming at the deficiencies, such as strong artificial dependence, low intelligence degree, low efficiency in disaster real-time judgement and early warning control decision etc., for safety management in Gaoliukeng tailing pond of Hunan Gold Group, a decision-making support system of tailing pond of tailing pond safety based on Internet of Things was studied and designed by combining Internet of Things technology with advanced data aware technology, and it achieved the comprehensive integration of multiple links including data collection, processing, analysis, decision-making and so on. It makes the participating parties in construction and operation of tailing pond enhance cognition and reveal the disaster regularity of tailing pond safety, and provides strong auxiliary support for realizing intelligent early warning and decision-making in safety management of tailing pond.
Keywords:tailing pond  Internet of Things  safety monitoring  data collection
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