SUN Jiping, YU Xingchen, WANG Yunquan, et al. Research on perception method of coal mine gas and coal dust explosion based on explosion sound recognition[J]. Journal of Mine Automation,2023,49(3):1-5, 114. DOI: 10.13272/j.issn.1671-251x.18077
Citation: SUN Jiping, YU Xingchen, WANG Yunquan, et al. Research on perception method of coal mine gas and coal dust explosion based on explosion sound recognition[J]. Journal of Mine Automation,2023,49(3):1-5, 114. DOI: 10.13272/j.issn.1671-251x.18077

Research on perception method of coal mine gas and coal dust explosion based on explosion sound recognition

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  • Received Date: February 11, 2023
  • Revised Date: March 12, 2023
  • Available Online: March 26, 2023
  • The characteristics of coal mine gas and coal dust explosion are analyzed. The gas concentration changes suddenly. The ambient temperature rises rapidly. The air pressure rises suddenly. It produces fireballs and smoke. It produces strong infrared and ultraviolet radiation. It generates explosion shock waves and flame waves. It produces explosive sound. The coal mine gas and coal dust explosion perception based on explosion sound has the following advantages. ① Explosion shock waves and flame waves attenuate quickly and travel close distances. Sound waves attenuate slowly and travel over long distances. The mine sound pickup equipment far away from the explosion source can be used for the perception of coal mine gas and coal dust explosion. ② Compared with the coal mine gas and coal dust explosion perception method based on gas concentration and temperature sensors, the proposed method has the advantage of fast response. ③ Compared with the coal mine gas and coal dust explosion perception method based on video images, the proposed method has the advantages of not being affected by dust, light, shelter, etc. ④ Mine sound pickup equipment has low cost and is easy to install. ⑤ The sound travels over a long distance and it is less affected by roadways and branches. ⑥ The sound processing speed is fast. The gas and coal dust explosion sound can be quickly recognized from various sound signals in a short time. A perception method of coal mine gas and coal dust explosion based on explosion sound recognition is proposed. The sound signals in the monitoring area are collected using microphone array pickups. After preprocessing such as normalization, framing, and adding category labels, the sound signal features are extracted. The features are input into a statistical classifier for training. The sound recognition model for coal mine gas and coal dust explosion is established. The sound signal of the monitoring area is collected in real-time. The extracted sound signal features are input into the trained coal mine gas and coal dust explosion sound recognition model. Whether it is the coal mine gas and coal dust explosion sound can be determined. If so, an alarm will be given.
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