Research on perception method of coal mine gas and coal dust explosion based on explosion sound recognition
-
摘要: 分析了煤矿瓦斯和煤尘爆炸特征:气体浓度发生突变;环境温度迅速升高;空气压力突然升高;产生火球和烟尘;产生较强的红外和紫外辐射;产生爆炸冲击波和火焰波;产生爆炸音。基于爆炸声音感知煤矿瓦斯和煤尘爆炸具有以下优点:① 爆炸冲击波和火焰波衰减快,传播距离近;声波衰减慢,传播距离远。远离爆源的矿用拾音设备可用于煤矿瓦斯和煤尘爆炸感知。② 与基于气体浓度和温度等传感器的煤矿瓦斯和煤尘爆炸感知方法相比,具有响应速度快的优点。③ 与基于视频图像的煤矿瓦斯和煤尘爆炸感知方法相比,具有不受粉尘、光照、遮挡等影响的优点。④ 矿用拾音设备成本低、易安装。⑤ 声音传播距离远,受巷道和分支影响小。⑥ 声音处理速度快,可在短时间内从各种声音信号中快速识别瓦斯和煤尘爆炸声音。提出了基于爆炸声音识别的煤矿瓦斯和煤尘爆炸感知方法:利用麦克风阵列拾音器采集监测区域的声音信号,经过归一化、分帧、添加类别标签等预处理后,提取声音信号特征,将特征输入到统计分类器中进行训练,建立煤矿瓦斯和煤尘爆炸声音识别模型;实时采集监测区域的声音信号,将提取的声音信号特征输入训练完成的煤矿瓦斯和煤尘爆炸声音识别模型中,判断是否为煤矿瓦斯和煤尘爆炸声音,若是则进行报警。Abstract: 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.
-
-
-
[1] 孙继平. 煤矿事故分析与煤矿大数据和物联网[J]. 工矿自动化,2015,41(3):1-5. DOI: 10.13272/j.issn.1671-251x.2015.03.001 SUN Jiping. Accident analysis and big data and Internet of things in coal mine[J]. Industry and Mine Automation,2015,41(3):1-5. DOI: 10.13272/j.issn.1671-251x.2015.03.001
[2] 孙继平,钱晓红. 煤矿事故与应急救援技术装备[J]. 工矿自动化,2016,42(10):1-5. DOI: 10.13272/j.issn.1671-251x.2016.10.001 SUN Jiping,QIAN Xiaohong. Coal mine accident and emergency rescue technology and equipment[J]. Industry and Mine Automation,2016,42(10):1-5. DOI: 10.13272/j.issn.1671-251x.2016.10.001
[3] 孙继平,钱晓红. 煤矿重特大事故应急救援技术及装备[J]. 煤炭科学技术,2017,45(1):112-116,153. DOI: 10.13199/j.cnki.cst.2017.01.019 SUN Jiping,QIAN Xiaohong. Emergency rescue technology and equipment of mine extraordinary accidents[J]. Coal Science and Technology,2017,45(1):112-116,153. DOI: 10.13199/j.cnki.cst.2017.01.019
[4] 孙继平,钱晓红. 2004—2015年全国煤矿事故分析[J]. 工矿自动化,2016,42(11):1-5. DOI: 10.13272/j.issn.1671-251x.2016.11.001 SUN Jiping,QIAN Xiaohong. Analysis of coal mine accidents in China during 2004-2015[J]. Industry and Mine Automation,2016,42(11):1-5. DOI: 10.13272/j.issn.1671-251x.2016.11.001
[5] 孙继平. 基于物联网的煤矿瓦斯爆炸事故防范措施及典型事故分析[J]. 煤炭学报,2011,36(7):1172-1176. DOI: 10.13225/j.cnki.jccs.2011.07.017 SUN Jiping. The accident prevention measure and analysis based on Internet of things in the gas explosion of coal mines[J]. Journal of China Coal Society,2011,36(7):1172-1176. DOI: 10.13225/j.cnki.jccs.2011.07.017
[6] 孙继平. 屯兰煤矿“2·22”特别重大瓦斯爆炸事故原因及教训[J]. 煤炭学报,2010,35(1):72-75. DOI: 10.13225/j.cnki.jccs.2010.01.020 SUN Jiping. The causes and lessons of "2·22" gas explosion disaster at Tunlan Coal Mine[J]. Journal of China Coal Society,2010,35(1):72-75. DOI: 10.13225/j.cnki.jccs.2010.01.020
[7] 孙继平. 煤与瓦斯突出报警方法[J]. 工矿自动化,2014,40(11):1-5. DOI: 10.13272/j.issn.1671-251x.2014.11.001 SUN Jiping. Alarm methods of coal and gas outburst[J]. Industry and Mine Automation,2014,40(11):1-5. DOI: 10.13272/j.issn.1671-251x.2014.11.001
[8] 孙继平. 煤矿井下安全避险“六大系统”的作用和配置方案[J]. 工矿自动化,2010,36(11):1-4. SUN Jiping. Effect and configuration of "Six Systems" for safe act of rescue of coal mine underground[J]. Industry and Mine Automation,2010,36(11):1-4.
[9] 孙继平. 煤矿信息化与自动化发展趋势[J]. 工矿自动化,2015,41(4):1-5. DOI: 10.13272/j.issn.1671-251x.2015.04.001 SUN Jiping. Development trend of coal mine informatization and automation[J]. Industry and Mine Automation,2015,41(4):1-5. DOI: 10.13272/j.issn.1671-251x.2015.04.001
[10] 孙继平. 煤矿监控新技术与新装备[J]. 工矿自动化,2015,41(1):1-5. DOI: 10.13272/j.issn.1671-251x.2015.01.001 SUN Jiping. New technologies and new equipments of coal mine monitoring[J]. Industry and Mine Automation,2015,41(1):1-5. DOI: 10.13272/j.issn.1671-251x.2015.01.001
[11] 孙继平. 煤矿信息化与智能化要求与关键技术[J]. 煤炭科学技术,2014,42(9):22-25,71. DOI: 10.13199/j.cnki.cst.2014.09.005 SUN Jiping. Requirement and key technology on mine informationalization and intelligent technology[J]. Coal Science and Technology,2014,42(9):22-25,71. DOI: 10.13199/j.cnki.cst.2014.09.005
[12] 孙继平. 煤矿瓦斯和煤尘爆炸感知报警与爆源判定方法研究[J]. 工矿自动化,2020,46(6):1-5,11. DOI: 10.13272/j.issn.1671-251x.17617 SUN Jiping. Research on method of coal mine gas and coal dust explosion perception alarm and explosion source judgment[J]. Industry and Mine Automation,2020,46(6):1-5,11. DOI: 10.13272/j.issn.1671-251x.17617
[13] 孙继平,余星辰. 基于声音识别的煤矿重特大事故报警方法研究[J]. 工矿自动化,2021,47(2):1-5,44. DOI: 10.13272/j.issn.1671-251x.17715 SUN Jiping,YU Xingchen. Research on alarm method of coal mine extraordinary accidents based on sound recognition[J]. Industry and Mine Automation,2021,47(2):1-5,44. DOI: 10.13272/j.issn.1671-251x.17715
[14] 孙继平,范伟强. 基于视频图像的瓦斯和煤尘爆炸感知报警及爆源判定方法[J]. 工矿自动化,2020,46(7):1-4,48. DOI: 10.13272/j.issn.1671-251x.17629 SUN Jiping,FAN Weiqiang. Gas and coal dust explosion perception alarm and explosion source judgment method based on video image[J]. Industry and Mine Automation,2020,46(7):1-4,48. DOI: 10.13272/j.issn.1671-251x.17629
[15] 孙继平,余星辰. 基于CEEMD分量样本熵与SVM分类的煤矿瓦斯和煤尘爆炸声音识别方法[J]. 采矿与安全工程学报,2022,39(5):1061-1070. DOI: 10.13545/j.cnki.jmse.2022.0073 SUN Jiping,YU Xingchen. Sound recognition method of coal mine gas and coal dust explosion based on CEEMD component sample entropy and SVM classification[J]. Journal of Mining & Safety Engineering,2022,39(5):1061-1070. DOI: 10.13545/j.cnki.jmse.2022.0073
[16] 孙继平,余星辰. 基于声音特征的煤矿瓦斯和煤尘爆炸识别方法[J]. 中国矿业大学学报,2022,51(6):1096-1105. DOI: 10.13247/j.cnki.jcumt.001451 SUN Jiping,YU Xingchen. Recognition method of coal mine gas and coal dust explosion based on sound characteristics[J]. Journal of China University of Mining & Technology,2022,51(6):1096-1105. DOI: 10.13247/j.cnki.jcumt.001451
[17] 余星辰,王云泉. 基于小波包能量的煤矿瓦斯和煤尘爆炸声音识别方法[J]. 工矿自动化,2023,49(1):131-139. DOI: 10.13272/j.issn.1671-251x.18070 YU Xingchen,WANG Yunquan. Coal mine gas and coal dust explosion sound recognition method based on wavelet packet energy[J]. Journal of Mine Automation,2023,49(1):131-139. DOI: 10.13272/j.issn.1671-251x.18070
[18] 周心权,吴兵,徐景德. 煤矿井下瓦斯爆炸的基本特性[J]. 中国煤炭,2002,28(9):8-11,4. DOI: 10.19880/j.cnki.ccm.2002.09.002 ZHOU Xinquan,WU Bing,XU Jingde. Basic characters of gas explosion in underground coal mines[J]. China Coal,2002,28(9):8-11,4. DOI: 10.19880/j.cnki.ccm.2002.09.002
[19] 景国勋,彭乐,班涛,等. 甲烷煤尘耦合爆炸传播特性及伤害研究[J]. 中国安全科学学报,2022,32(1):72-78. DOI: 10.16265/j.cnki.issn1003-3033.2022.01.010 JING Guoxun,PENG Le,BAN Tao,et al. Research on pressure propagation and injury of methane and coal dust coupled explosion[J]. China Safety Science Journal,2022,32(1):72-78. DOI: 10.16265/j.cnki.issn1003-3033.2022.01.010
[20] 江丙友,林柏泉,陈健,等. 瓦斯爆燃防爆安全距离及传播特征的数值模拟[J]. 采矿与安全工程学报,2014,31(1):139-145. DOI: 10.13545/j.issn1673-3363.2014.01.023 JIANG Bingyou,LIN Baiquan,CHEN Jian,et al. Numerical simulation of explosion-proof safety distance and propagation characteristics of gas deflagration[J]. Journal of Mining & Safety Engineering,2014,31(1):139-145. DOI: 10.13545/j.issn1673-3363.2014.01.023
[21] 彭佑多,谢伟华,郭迎福,等. 矿井掘进工作面粉尘对机器噪声衰减的影响[J]. 湖南科技大学学报(自然科学版),2012,27(1):23-29. DOI: 10.3969/j.issn.1672-9102.2012.01.005 PENG Youduo,XIE Weihua,GUO Yingfu,et al. Studies on the spread and attenuation of machine noise influenced by the heading face of mine roadway dust[J]. Journal of Hunan University of Science and Technology(Natural Science Edition),2012,27(1):23-29. DOI: 10.3969/j.issn.1672-9102.2012.01.005
-
期刊类型引用(20)
1. 刘相通,李曼,沈思怡,曹现刚,刘俊祺. 液压支架关键姿态参数测量系统. 工矿自动化. 2024(04): 41-49 . 本站查看
2. 文治国. 四柱支撑掩护式液压支架支护状态分析计算. 煤矿机械. 2023(04): 23-26 . 百度学术
3. 张坤,孙政贤,刘亚,李玉霞,杜明超,马英,魏训涛,徐亚军,王鑫,余铜柱,丁超. 基于信息融合技术的超前液压支架姿态感知方法及实验验证. 煤炭学报. 2023(S1): 345-356 . 百度学术
4. 权钰涵,张啸,刘冬,罗睿,贺云. 融合激光SLAM实现平衡车智能导航. 电子技术应用. 2023(10): 141-147 . 百度学术
5. 庞义辉,刘新华,王泓博,姜志刚,关书方,张自发,王伟. 基于千斤顶行程驱动的液压支架支护姿态与高度解析方法. 采矿与安全工程学报. 2023(06): 1231-1242 . 百度学术
6. 王裕,史艳楠,王毅颖,齐朋磊,王翰秋. 固体充填液压支架全位姿测量及虚拟仿真. 工矿自动化. 2022(07): 81-89 . 本站查看
7. 卢金强. 矿井液压支架激光定位传感器的应用研究. 机械管理开发. 2022(09): 240-242 . 百度学术
8. 梁娜娜. 基于灰色理论的液压支架姿态监测方法研究. 煤矿机械. 2021(05): 191-193 . 百度学术
9. 胡相捧,刘新华. 初撑阶段的支架位姿与驱动千斤顶一一映射及调整策略. 采矿与安全工程学报. 2021(04): 666-677 . 百度学术
10. 高有进,杨艺,常亚军,张幸福,李国威,连东辉,崔科飞,武学艺,魏宗杰. 综采工作面智能化关键技术现状与展望. 煤炭科学技术. 2021(08): 1-22 . 百度学术
11. 张雪梅. 基于无线传感数据的液压支架三维姿态监测. 山西焦煤科技. 2021(09): 31-35 . 百度学术
12. 郭春福,占晓祥,张宁,韩智儒. 井下液压支架运行姿态智能感知技术分析. 中国高新科技. 2021(18): 97-98 . 百度学术
13. 曹贯强,赵文生. 基于MEMS加速度计的高精度倾角传感器研制. 自动化仪表. 2020(03): 25-28+35 . 百度学术
14. 廉自生,袁祥,高飞,廖瑶瑶,郭永昌,赵瑞豪. 液压支架网络化智能感控方法. 煤炭学报. 2020(06): 2078-2089 . 百度学术
15. 白晋铭,王然风,付翔. 基于架间行走机器人的液压支架直线度测量方法. 工矿自动化. 2019(01): 45-51 . 本站查看
16. 张旭辉,王冬曼,杨文娟. 基于视觉测量的液压支架位姿检测方法. 工矿自动化. 2019(03): 56-60 . 本站查看
17. 王昕,李鹏鹏,沈行良. 基于影像的角度测量系统设计与实现. 智能计算机与应用. 2019(04): 271-273+277 . 百度学术
18. 马旭东,许春雨,宋建成. 综采工作面液压支架姿态监测系统设计. 煤炭技术. 2019(07): 174-177 . 百度学术
19. 许金星. 机器视觉的液压支架姿态角度测量系统设计. 煤矿机械. 2019(09): 11-13 . 百度学术
20. 张德生,任怀伟,何明,卞冀,李提建,马强. 两柱掩护式液压支架内外加载支护对比试验研究. 煤炭科学技术. 2019(11): 135-142 . 百度学术
其他类型引用(17)