College of Safety Science and Engineering,Xi’an University of Science and Technology
Key Laboratory of Western Mine Miningand Disaster Prevention and Control,Ministry of Education

为提升煤自燃火灾风险隐患的智能化防控能力和水平,实现煤自燃指标数据近场实时采集、智能分析与精准预警。通过采集多个矿区新鲜煤样,采用煤自燃程序升温试验、自然发火试验等手段,测定煤自然发火特征参数。结合煤自燃机理细化指标曲线特征点位,构建了I类容易自燃煤层分级预警模型,确定相关预警指标及阈值。设计研发ZDC7型矿井火灾智能监测预警系统,主要包括矿用本安型多参数无线传感器(GD7)、矿用本安型无线监测主机(ZDC7-Z)、智能管控软件平台等。矿用多参数传感器能够独立近场采集数据(CO,CH4,CO2,O2,H2S,温湿度和压差等),利用监测主机采用的带状受限空间能量有效的容错拓扑控制技术与开放无线感知网络协议标准,确保ZDC7系统便捷地融入煤矿井下工业环网,同时有效、稳定地保障数据信息传输至多终端(手机APP、地面工控机、井下交互界面等)。智能管控软件平台内嵌智能分析预警模块,能够结合深度学习和多元回归分析等理论以实现多源信息融合自处理,智能分析火灾预警级别和煤自燃异常区域态势预测,并根据监测信息的预处理分析实现火灾防控技术方案的辅助决策支持。作为一种在线实时感知煤自燃特征信息、智能识别判定煤自燃程度、内嵌煤自燃分级预警与辅助决策模型的矿井火灾智能监测预警系统,已开展现场工业试验与应用,技术装备符合国家智能化矿井建设的相关规范和标准,满足煤矿企业对矿井火灾的智能化监测预警与防控工作实际需求,可有效保障煤矿企业的绿色安全开采。

In order to improve the ability and level of intelligent prevention and control on the hidden danger of coalspontaneous combustion fire,the near⁃field real⁃time collection,intelligent analysis and accurate early warning of coalspontaneous combustion index data are realized. By collecting fresh coal samples from multiple mining areas,the evo⁃lution characteristics of coal spontaneous combustion characteristic parameters were determined by means of coal spon⁃taneous combustion temperature⁃programmed heating and spontaneous ignition tests. Combined with the characteristicpoints of the coal spontaneous combustion mechanism refinement index curve,a graded early warning model of the typeI coal seam prone to spontaneous combustion is constructed,and the relevant early warning indicators and thresholdsare determined. The ZDC7 mine fire intelligent monitoring and early warning system has been designed anddeveloped,including mine intrinsically safe multi⁃parameter wireless sensor ( GD7), mine intrinsically safe wire⁃less monitoring host (ZDC7-Z),and intelligent management and control software platform. Mining multi⁃parametersensors can independently collect data in the near field ( CO, CH4, CO2, O2, H2 S, temperature and humidity,differential pressure,etc.). In order to ensure that the ZDC7 system can be easily integrated into the underground in⁃dustrial ring network of coal mines and effectively and stably ensure the transmission of data and information to multi⁃ple terminals ( mobile phone APP, ground industrial computer, underground interactive interface, etc.), the band⁃shaped confined space energy efficient fault⁃tolerant topology control technology and the open wireless sensing networkprotocol standard adopted by the monitoring host can be used. In order to realize multi⁃source information fusion andself⁃processing,intelligently analyze the fire warning level and abnormal coal spontaneous combustion area situationprediction,an intelligent analysis and early warning module embedded in the intelligent management and control soft⁃ware platform is used,combined with deep learning and multiple regression analysis and other theories,and basedon monitoring information. The preprocessing analysis of the method realizes the auxiliary decision support of the fireprevention and control technical scheme. As a mine fire intelligent monitoring and early warning system, it isembedded with a coal spontaneous combustion classification early warning and auxiliary decision⁃making model,which can sense the coal spontaneous combustion characteristic information online in real⁃time,and intelligently identi⁃fy and assess the coal spontaneous combustion degree. Its on⁃site industrial tests and applications have been carriedout,and its technical equipment conforms to the relevant national norms and standards for the construction ofintelligent mines. The actual needs of coal mining enterprises for intelligent monitoring,early warning and preventionand control of mine fires have been met,and the green safe mining of coal mining enterprises is effectively guaranteed.

国家自然科学基金青年科学基金资助项目(52004209);国家自然科学基金面上资助项目(52174198)

郭军,王凯旋,金永飞,等. 煤自燃进程精细划分方法及其智能监测预警———煤火精准防控技术变革[J].煤炭学报,2023,48(S1):111-129.

GUO Jun,WANG Kaixuan,JIN Yongfei,et al. Fine division method of coal spontaneous combustion process andits intelligent monitoring and early warning:Technological change in precise prevention and control of coal fires[J]. Journal of China Coal Society,2023,48(S1):111-129