矿井大数据分析及职工不安全行为预控研究
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摘要
针对现代化矿井生产过程中产生的各类数据,从大数据的理念出发,定义了矿井大数据的概念;对矿井大数据的来源与分类进行了概述和归纳。提出矿井大数据的两个重要潜在价值:以大量历史数据为支撑总结形成的规律与经验,以实时数据信息为基础进行危险的预判预控。以职工不安全行为控制为目标,通过分析挖掘矿井实时监测数据信息的潜在价值,尤其是数据内部隐含信息所表征出的危险程度,构建基于大数据处理的职工不安全行为预判控制模式。提出以数据吻合度和突变点为基础的数据处理模式和流程,并设计职工不安全行为预控的三种作业模式。
Based on varieties of data produced in the manufacturing process of modern coal mine and the idea of big data,this paper defines the concept of big data in coal mine and summarizes its sources and classifications.Two important potential values of big data in coal mine were put forward:to find regularity and experience based on large quantities of historical data and to predict and pre-control hazards based on real-time big data.With pre-control of coal mine workers' unsafe behaviors as target,prediction and pre-control models of unsafe behaviors based on big data processing were constructed by analyzing the real-time monitoring data in coal mine,especially the degree of hazard implied by the hidden information within the data.Data processing model and procedures based on goodness of fit to data and catastrophe point were proposed and three pre-control work patterns of coal mine workers' unsafe behaviors were designed.
引文
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