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Research on Monitoring and Prewarning System of Accident in the Coal Mine Based on Big Data

机译:基于大数据的煤矿事故监测与预警系统研究

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摘要

More and more big data come from sensor nodes. There are many sensor nodes placed in the monitoring and prewarning system of the coal mine in China for the purpose of monitoring the state of the environment. It works every day and forms the coal mine big data. Traditional coal mine monitoring and prewarning systems are mainly based on mine communication cable, but they are difficult to place at coal working face tunnels. We use WSN to replace mine communication cable and build the monitoring and prewarning system. The sensor nodes in WSN are energy limited and the sensor data are complicated so it is very difficult to use these data directly to prewarn the accident. To solve these problems, in this paper, a new data aggregation strategy and fuzzy comprehensive assessment model are proposed. Simulations compared the energy consumption, delay time, cooperation cost, and prewarning time with our previous work. The result shows our method is reasonable.
机译:越来越多的大数据来自传感器节点。为了监视环境状况,在中国的煤矿监视和预警系统中放置了许多传感器节点。它每天工作,并构成煤矿的大数据。传统的煤矿监控预警系统主要基于矿井通讯电缆,但是很难放置在采煤工作面巷道中。我们使用WSN替换矿山通信电缆,并建立监视和预警系统。 WSN中的传感器节点受能量限制,并且传感器数据复杂,因此很难直接使用这些数据来预警事故。为了解决这些问题,本文提出了一种新的数据聚合策略和模糊综合评价模型。仿真将能耗,延迟时间,合作成本和预警时间与我们以前的工作进行了比较。结果表明我们的方法是合理的。

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