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。
The current coal industry faces difficulties due to the decline of macroeconomic growth rate.It's difficult to improve the operational efficiency of coal enterprises by traditional production and management mode,so there is urgent need for coal enterprises to transform and upgrade themselves,and use the Internet,big data,cloud computing and other modern information means to reconstruct production and management mode. At the same time,In response to the national "Internet + smart energy"action to improve the coal mine safety and stable operation level and promote energy production more intelligent.Using big data technology we analyze and predict the status of the equipment and other data. In this paper,we design a practical method to identify belt faults by using large data,information fusion and gray correlation method,which is important to improve the efficiency of the belt and reduce the economic losses caused by the failure of belt.