[1]罗 波,张金锁,邢书宝.大数据煤矿胶带输送机速度状态评估模型设计[J].西安科技大学学报,2016,(02):176-180.
 LUO Bo,ZHANG Jin-suo,XING Shu-bao.Design of speed state evaluation model of coal mine belt conveyor based on big data[J].Journal of Xi'an University of Science and Technology,2016,(02):176-180.
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2016年02期
页码:
176-180
栏目:
出版日期:
2016-04-11

文章信息/Info

Title:
Design of speed state evaluation model of coal mine belt conveyor based on big data
文章编号:
10.13800/j.cnki.xakjdxxb.2016.0205
作者:
罗 波12张金锁3邢书宝4
1.西安科技大学 能源学院,陕西 西安 710054; 2.西安科技大学 能源与经济管理研究中心,陕西 西安 710054; 3.延安大学 经济管理学院,陕西 延安 716000; 4.西安科技大学 管理学院,陕西 西安 710054
Author(s):
LUO Bo12ZHANG Jin-suo3XING Shu-bao4
1. College of Energy Science and Engineering,Xi'an University of Science and Technology,Xi'an 710054,China; 2.Research Center for Energy Economic and Management,Xi'an University of Science and Technology,Xi'an 710054,China; 3. College of Economics and Management,Yan'an University,Yan'an 716000,China; 4. College of Management,Xi'an University of Science and Technology,Xi'an 710054,China
关键词:
大数据 信息融合 灰色关联分析 皮带输送机
Keywords:
big data information fusion gray correlation analysis belt conveyor
分类号:
TD 528; X 936
文献标志码:
A
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:
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 needfor 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.

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备注/Memo

备注/Memo:
收稿日期:2015-11-05 责任编辑:李克永 基金项目:国家自然科学基金(71273206,71273207) 通讯作者:张金锁(1962-),男,陕西凤翔人,教授,博导,E-mail:mark56zhang@163.com
更新日期/Last Update: 1900-01-01