基于声音识别的煤矿重特大事故报警方法研究

Research on alarm method of coal mine extraordinary accidents based on sound recognitio

  • 摘要: 煤矿瓦斯与煤尘爆炸会产生爆炸声,煤与瓦斯突出会产生煤炮声、支架发出的嘎嘎声和破裂折断声等,冲击地压会产生巨大的岩石破碎声响和震动等,煤矿透水会发出“嘶嘶”的水叫声、大量透水会产生水流声等,煤矿顶板冒落会发出顶板断裂声、煤岩落地撞击声、支护损毁声等。针对煤矿重特大事故声音特点,提出了煤矿井下瓦斯与煤尘爆炸、煤与瓦斯突出、冲击地压、水灾、顶板冒落等事故报警方法:各事故声音的时域和频域特征与其他声音不同,可通过矿用防爆拾音设备和系统实时监测声音,通过声音智能分析和声音频率、幅度、短时能量等特征参数分析感知事故并报警;通过监测和分析不同监测地点声音强度特征、声音发生的先后关系和防爆拾音设备损坏的先后关系等判定事故发生地点;根据各事故特点提出了多信息融合分析的灾害识别方法,减小工作面落煤、爆破作业、采煤设备、掘进设备、运输提升设备、供电设备、乳化液泵、水泵和局部通风机工作等产生的声音干扰。论述了不同拾音设备的优缺点,矿用拾音设备宜采用麦克风阵列;研究了适用于煤矿重特大事故的声音识别分类器。

     

    Abstract: Coal mine gas and coal dust explosion will produce explosive sound. Coal and gas outburst will produce the sound of coal cannon and the supports will produce squeaking and cracking sound. Rock burst will produce huge rock breaking sound and vibrations. Coal mine water inrush will produce "hissing" water sound, and a large amount of water inrush will produce water flow sound. Coal mine roof fall will produce roof cracking sound, coal rock hitting the ground sound and support damage sound. According to the characteristics of the sound of extraordinary accidents in coal mines, the alarm methods of accidents of mine gas and coal dust explosion, coal and gas outburst, rock burst, water inrush and roof fall are proposed. The characteristics of the time domain and frequency domain of each accident sound are different from the characteristics of other sounds, and the sound can be monitored in real time by mine explosion-proof sound pickup equipment and system. Therefore, accidents can be sensed and alarmed through the intelligent analysis of the sound and the analysis of the characteristic parameters of the sound frequency, amplitude and short-term energy. By monitoring and analyzing the sound intensity and other characteristics of different monitoring locations, the sequence of occurrence and the damage sequence of explosion-proof sound pickup equipment, the accident location is able to be determined. Based on the characteristics of each accident, the accident identification method of multi-information fusion analysis is proposed to reduce the sound interference of coal fall from the working face, blasting operations, coal mining equipment, excavation equipment, transportation and lifting equipment, power supply equipment, emulsion pumps, water pumps and local ventilators. The paper discusses the advantages and disadvantages of different sound pickup equipment and proposes that the microphone arrays should be used for mine sound pickup equipment. Furthermore, the paper proposes a sound recognition classifier applicable to coal mine extraordinary accidents.

     

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