大数据煤矿胶带输送机速度状态评估模型设计

发布时间：2018-05-01 05:02

本文选题：大数据 + 信息融合　；参考：《西安科技大学学报》2016年02期

【摘要】：当前煤炭行业由于宏观经济增长速度的下滑出现困难,传统的生产、管理模式对提升企业的经营效率难有作为,煤炭企业亟需转型升级,利用互联网、大数据、云计算等现代信息手段重构生产、管理模式势在必行。同时,中国"互联网+智慧能源"行动在能源企业运用大数据技术对设备状态等数据进行分析挖掘与预测,推进能源生产智能化,对进一步提高煤矿安全稳定运行水平具有重要意义。通过运用大数据、信息融合和灰色关联法,设计了一种甄别皮带故障的实用方法。实验结果表明,该方法对提高皮带使用效率,降低因皮带损坏导致停工而产生的经济损失具有十分重要的应用价值。
[Abstract]:At present, the coal industry is facing difficulties due to the decline in the rate of macroeconomic growth, and the traditional production and management modes are difficult to improve the business efficiency of enterprises. Coal enterprises urgently need to be transformed and upgraded, using the Internet, big data, Cloud computing and other modern information means to restructure production, management mode is imperative. At the same time, China's "Internet Smart Energy" initiative has used big data technology to analyze and forecast equipment status data in energy enterprises, in order to promote intelligent energy production. It is of great significance to further improve the safety and stability of coal mine operation level. By using big data, information fusion and grey correlation method, a practical method for identifying belt faults is designed. The experimental results show that this method has important application value in improving the efficiency of belt use and reducing the economic loss caused by belt damage.
【作者单位】：西安科技大学能源学院;西安科技大学能源与经济管理研究中心;延安大学经济管理学院;西安科技大学管理学院;
【基金】：国家自然科学基金(71273206,71273207)
【分类号】：TD634.1

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