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煤与瓦斯突出预警技术研究现状及发展趋势
Research status of early warning technology of coal and gas outburst and its development trend
【索引】宁小亮.煤与瓦斯突出预警技术研究现状及发展趋势[J].工矿自动化,2019,45(8):25-31.
【Reference】NING Xiaoliang.Research status of early warning technology of coal and gas outburst and its development trend[J].Industry and Mine Automation,2019,45(8):25-31.
【DOI】10.13272/j.issn.1671-251x.17464
【作者】 宁小亮1,2
【Author】 NING Xiaoliang1,2
【作者机构】1.瓦斯灾害监控与应急技术国家重点实验室, 重庆400037;2.中煤科工集团重庆研究院有限公司, 重庆400037
【Unit】1.State Key Laboratory of the Gas Disaster Detecting, Preventing and Emergency Controlling, Chongqing 400037, China; 2.CCTEG Chongqing Research Institute, Chongqing 400037, China
【摘要】从煤与瓦斯突出灾害预警理论、预警信息采集途径、预警指标与模型、预警软件系统4个方面对煤与瓦斯突出预警技术的研究成果进行了综合梳理和详细分析,指出了现有煤与瓦斯突出预警技术存在的问题:部分预警信息获取的时效性和可靠性有待进一步提高,预警模型未实现信息有效深度挖掘等;提出了煤与瓦斯突出预警技术的发展趋势:高自动化水平、高精度的突出预警信息监测采集技术及装备研发,基于大数据的突出预警指标与模型研究,基于云技术的突出预警软件系统开发。
【Abstract】Research achievements of early warning technology of coal and gas outburst were summarized and analyzed in detail from four aspects: early warning theory of coal and gas outburst, acquisition means of early warning information, early warning index and model and early warning software system. The main problems of existing early warning technology of coal and gas outburst were pointed out, for example, timeliness and reliability of part early warning information acquisition needed to be further improved, early models could not realize effective and deep data mining, etc. Development trend of early warning technology of coal and gas outburst was put forward, including development of early warning information monitoring and acquisition technology and equipment with high automation level and precision, research of early warning index and model based on big data, and development of early warning software system based on cloud technology.
【关键词】 煤与瓦斯突出; 煤与瓦斯突出预警; 预警理论; 预警信息采集; 预警指标; 预警模型; 预警软件系统
【Keywords】coal and gas outburst; early warning of coal and gas outburst; early warning theory; early warning information acquisition; early warning index; early warning model; early warning software system
【文献出处】工矿自动化,2019年8期
【基金】国家重点研发计划资助项目(2018YFC0808305)
【分类号】TD713
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