煤与瓦斯突出预警方法探讨

赵旭生, 宁小亮, 张庆华, 马国龙

赵旭生,宁小亮,张庆华,等.煤与瓦斯突出预警方法探讨[J].工矿自动化,2018,44(1):6-10.. DOI: 10.13272/j.issn.1671-251x.17287
引用本文: 赵旭生,宁小亮,张庆华,等.煤与瓦斯突出预警方法探讨[J].工矿自动化,2018,44(1):6-10.. DOI: 10.13272/j.issn.1671-251x.17287
ZHAO Xusheng, NING Xiaoliang, ZHANG Qinghua, MA Guolong. Discussion on early warning method of coal and gas outburst[J]. Journal of Mine Automation, 2018, 44(1): 6-10. DOI: 10.13272/j.issn.1671-251x.17287
Citation: ZHAO Xusheng, NING Xiaoliang, ZHANG Qinghua, MA Guolong. Discussion on early warning method of coal and gas outburst[J]. Journal of Mine Automation, 2018, 44(1): 6-10. DOI: 10.13272/j.issn.1671-251x.17287

煤与瓦斯突出预警方法探讨

基金项目: 

国家重点研发计划资助项目(2016YFC0801404)

重庆市“科技创新领军人才支持计划”资助项目(CSTCKJCXLJRC14)

中国煤炭科工集团有限公司科技创新基金资助项目(2013ZD002)

详细信息
  • 中图分类号: TD713

Discussion on early warning method of coal and gas outburst

  • 摘要: 给出了煤与瓦斯突出预警的定义,明确指出了突出预警与预测的区别;从空间、时间和指标体系的角度对突出预警进行了分类,并根据突出灾害特点提出了突出预警应该具有的特征;以系统论和事故理论为指导,分析了突出预警系统构成和实现途径,并阐述了从警源监测、警兆识别、警情分析、警度发布和预警响应5个方面进行突出预警的步骤,同时给出了采用预警总准确率、漏报率和虚报率3个指标进行预警效果评价的方法。现场应用结果表明,所提突出预警方法的平均状态预警总准确率为89.1%,平均趋势预警总准确率为92.5%,漏报率为0。
    Abstract: Definition of early warning of coal and gas outburst was given, and difference between the early warning and forecasting was clearly pointed out. The early warning of coal and gas outburst was classified from angle of space, time and index system, and features of the early warning were put forward according to specific characteristics of coal and gas outburst disaster. System structure and implementation of the early warning were analyzed guided by system theory and accident theory. Steps of the early warning were described from five aspects of detection of risk source, warning sign identification, analysis of warning situation, alert release and early warning response. Method of effect evaluation of the early warning was put forward by using three indicators of initial warning accuracy, false negative rate and false alarm rate. The field application results show that the average accuracy rate of state warning is 89.1%, the average accuracy rate of trend warning is 92.5%, and the false negative rate is 0.
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    其他类型引用(6)

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出版历程
  • 刊出日期:  2018-01-09

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