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张文军, 王建平, 范世平, 杨春满, 李丽莉. 深井冻结施工远程监测与故障诊断物联网的设计[J]. 煤炭科学技术, 2015, (4).
引用本文: 张文军, 王建平, 范世平, 杨春满, 李丽莉. 深井冻结施工远程监测与故障诊断物联网的设计[J]. 煤炭科学技术, 2015, (4).
ZHANG Wen-jun WANG Jian-ping FAN Shi-ping YANG Chun-man LI L-li, . Design on internet of things for remote monitoring and fault diagnosis in deep mine shaft freezing construction[J]. COAL SCIENCE AND TECHNOLOGY, 2015, (4).
Citation: ZHANG Wen-jun WANG Jian-ping FAN Shi-ping YANG Chun-man LI L-li, . Design on internet of things for remote monitoring and fault diagnosis in deep mine shaft freezing construction[J]. COAL SCIENCE AND TECHNOLOGY, 2015, (4).

深井冻结施工远程监测与故障诊断物联网的设计

Design on internet of things for remote monitoring and fault diagnosis in deep mine shaft freezing construction

  • 摘要: 针对千米深井冻结施工的Internet远程监测与故障诊断的技术难题,提出了基于富互联网RIA技术的物联网架构:在传感层,研发了测量深度突破千米的"自适应寻优驱动一总线"18B20测温算法和节点模块;在网络传输层,实现了现场实时传感数据的汇总和重组,并传送至位于云环境中物联网中间件;在应用层中,提出了基于自学习概率统计的故障识别诊断算法,开发了物联网中间件与数据中心Web Service、基于Flex代理和Java EE的Web应用系统,以及基于Flex强交互性的Web人机界面。最终成功地应用于1 200 m深的陕西核桃峪矿深井冻结施工项目,实践表明:该物联网系统能够通过Internet远程监测冻结工程中1 200 m深井的实时数据,进行故障识别诊断,实现数据的曲线图表可视化,以及历史数据的统计分析与管理,能有效地远程指导冻结施工。

     

    Abstract: According to the technical difficultes of the internet remote monitoring and fault diagnosis for over 1 000 m deep mine shaft freezing construction,based on the rich internet RIA technology,an internet of things framework was provided. In the sensing layer,an"adaptive optimization driving- bus" 18B20 thermometry algorithm and node module were researched and developed with a measuring depth over 1 000 m. In the network transmission layer,a collection and recombination of site real time sensi ng data were realized and then the data would be transmitted to the middle ware of the internet of things in the cloud environment. In the application layer,based on the self learning probability statistics,a fault recognition and diagnosis algorithm was provided and the middleware of internet of things and the data center Web Service were devel oped based on the Flex agent and the Web application system of Java EE as well as based on the Flex strong interactivity Web man- machine interface. Finally,the internet of things and software were successfully applied to the deep mine shaft freezing construction project of Hetaoyu Mine with depth of 1 200 m,Shaanxi. The practices showe d that the internet of things system could remotely monitor and measure the real time data of the 1 200 m depth in freezing project with the internet. A fault recognition and diagnosis was conducted and visualization of the data curve diagram could be realized. A statistical analysis and management of the historical data could be effectively app lied to the remote guidance of freezing construction.

     

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