Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation

Safety in Coal Mines > 2022 > 53(9): 47-54.

Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation[J]. Safety in Coal Mines, 2022, 53(9): 47-54.

Citation:

Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation[J]. Safety in Coal Mines, 2022, 53(9): 47-54.

Citation:

Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation[J]. Safety in Coal Mines, 2022, 53(9): 47-54.

PDF (2599 KB)

Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation

More Information

Published Date: September 19, 2022

Graphical Abstract

Abstract

Abstract

Starting from the perspective of method principle, system application, and technical characteristics, this paper systematically discussed the research progress of intelligent monitoring and early warning technology concerning fire risk of belt transportation, including inspection technology, distributed optical fiber temperature measurement technology, machine vision technology, wireless communication network technology and data-driven technology. Moreover, the advantages and disadvantages of those monitoring and early warning technologies were discussed. Based on the existing monitoring means of coal mine roadway and the development hotspot of digital intelligence, we proposed a new intelligent monitoring and early warning system for mine belt transportation fire and early warning: “Big-Intelligent-Mobile-Cloud” （big data, intelligent, mobile internet, and cloud computing respectively） coal mine belt fire monitoring system and multi-method coupling, three-dimensional, continuous monitoring system.
- belt transportation fire,
- monitoring system,
- intelligent monitoring,
- data driven,
- prediction and early warning

FullText(HTML)

References (55)

References

[1]	王德明.煤矿热动力灾害及特性[J]．煤炭学报，2018， 43（1）：137-142. WANG Deming. Thermodynamic disaster in coal mine and its characteristics[J]. Journal of China Coal Society, 2018, 43（1）: 137-142.
[2]	赵志强.矿用带式输送机的使用及故障分析[J].当代化工研究，2019（12）：17-18. ZHAO Zhiqiang. Application and fault analysis of mining belt conveyor[J]. Modern Chemical Research, 2019（12）: 17-18.
[3]	王烨.矿井胶带火灾烟流蔓延特性与监测方法研究[D].西安：西安科技大学，2021.
[4]	李志宪，陈江.日本三井三池有明煤矿井下特大火灾事故[J].工业安全与防尘，1990（3）：42.
[5]	郑宝莲.煤矿外因火灾的原因及其防控[J].科技创新导报，2017，14（2）：55.
[6]	黑龙江龙煤集团鸡西杏花煤矿“11·20”井下火灾事故抢险救援纪实[J].中国应急管理，2015 （11）：56.
[7]	重庆松藻煤矿“9·27”重大火灾事故37名公职人员被追责问责[J].消防界（电子版），2021，7（7）：44.
[8]	崔健.基于WSN的矿井皮带传输机火灾监测节点的研究[D].阜新：辽宁工程技术大学，2014.
[9]	黄民，顾玉华，魏任之.矿用胶带输送机火灾监测系统的研究[J].煤炭学报，2002（1）：78-82. HUANG Min, GU Yuhua, WEI Renzhi. Study on system for monitoring mine belt conveyor fire[J]. Journal of China Coal Society, 2002（1）: 78-82.
[10]	Wang Chuanwei, Ma Hongwei, Shang Wanfeng, et al. Modeling and Simulation of the Inspection Robot for Belt Conveyor[C]//Proceedings of 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference （ITOEC 2017）. IEEE, 2017: 322-325.
[11]	Zhen L I, Cao H, Jia H G, et al. Bearing Monitoring and Diagnosis System of Belt Conveyor of Coal Mine and Its Application[J]. Industry & Mine Automation, 2011, 11（18）: 9451-9463.
[12]	曹军.带式输送机巡检机器人设计与研究[D].徐州：中国矿业大学，2019.
[13]	徐晋伟.矿山胶带运输智能巡检机器人的探索与应用[J].矿业工程，2020，18（4）：62-64. XU Jinwei. Exploration and application of intelligent inspection robot for belt conveyingin mines[J]. Mining Engineering, 2020, 18（4）: 62-64.
[14]	靳子浩.矿用悬挂式巡检机器人设计[D].西安：西安科技大学，2017.
[15]	李湘闽，张慧兰.矿山电动轮运输车辆加油系统改造及管理系统智能化[J].矿山机械，2006（6）：69-.
[16]	李伟，江帆，朱真才，等.一种悬索式带式输送机自动巡检系统：CN102923466B[P].2014-10-29.
[17]	李伟，任勇，龚男，等.一种基于多旋翼无人机的带式输送机自动巡检系统及方法：CN103869819A[P].2014-06-18.
[18]	王彦，黄晓东，黄朝晖.煤矿带式输送机智能巡检系统的设计与应用[J].煤矿机电，2014（2）：39-41. WANG Yan, HUANG Xiaodong, HUANG Zhaohui. Design and application of intelligent route inspectionsystem in belt conveyor[J]. Colliery Mechanical & Electrical Technology, 2014（2）: 39-41.
[19]	张永，赵伟.井下胶带机道自动巡检机器人的研究与应用[J].能源与环保，2021，43（9）：36-40. ZHANG Yong, ZHAO Wei. Research and application of automatic inspection robot for underground belt conveyor road[J]. China Energy and Environmental Protection, 2021, 43（9）: 36-40.
[20]	朱振.带式输送机托辊运行状态在线巡检机器人关键技术研究[D].阜新：辽宁工程技术大学，2020.
[21]	闫惠芳.分布式光纤测温技术在煤矿安全中的应用[J].中国煤炭，2013，39（12）：72-74. YAN Huifang. Application of temperature measurement with distributed optical fibers to coal mine safety[J]. China Coal, 2013, 39（12）: 72-74.
[22]	于庆.分布式光纤测温技术在煤矿中的应用[J].工矿自动化，2012，38（4）：5-8. YU Qing. Application of distributed fiber temperature measurement technology in coal mine[J]. Industry and Mine Automation, 2012, 38（4）: 5-8.
[23]	张美金.基于RS-SVM算法的矿井主运输系统火灾诊断及灾害控制研究[D].阜新：辽宁工程技术大学，2016.
[24]	程永新.煤矿带式输送机火灾光纤传感检测技术研究[J].煤炭科学技术，2019，47（2）：131. CHENG Yongxin. Technology research on optical fiber sensing detection forbelt conveyor fire in coal mine[J]. Coal Science and Technology, 2019, 47（2）: 131.
[25]	郭清华.基于光纤测温的托辊轴温检测及热传导模型研究[J].矿业安全与环保，2020，47（1）：66-69. GUO Qinghua. Research on roller shaft temperature detection and thermal conductivity model based on optical fiber temperature measurement[J]. Mining Safety & Environmental Protection, 2020, 47（1）: 66-69.
[26]	田秀德，冯军.分布式光纤测温技术在港口皮带机系统及筒仓温度监测中的应用[J].港口科技，2011（4）：11-14. TIAN Xiude, FENG Jun. The application of the distributed optical fiber temperature measurement in the monitoring of the belt system and the silo of port[J]. Port Science & Technology, 2011（4）: 11-14.
[27]	马宏伟，杨文娟，张旭辉.基于红外热像的带式输送机监测与预警系统[J].激光与红外，2017，47（4）：448-452. MA Hongwei, YANG Wenjuan, ZHANG Xuhui. Monitoring and warning system of belt conveyor based on infrared thermography[J]. Laser & Infrared, 2017, 47（4）: 448-452.
[28]	冯加宇，唐洪，贺涛，等.基于红外热成像的煤矿输送带火灾监测预警技术研究[J].煤炭技术，2016， 35（12）：280-282. FENG Jiayu, TANG Hong, HE Tao, et al. Infrared image monitoring and early-warning technology of coal-mine conveyor belt fire[J]. Coal Technology, 2016, 35（12）: 280-282.
[29]	马宏伟，杨文娟，张旭辉.带式输送机托辊红外图像分割与定位算法[J].西安科技大学学报，2017，37（6）：892. MA Hongwei, YANG Wenjuan, ZHANG Xuhui. Segmentation and location algorithm for infraredimage of roller on conveyor belt[J]. Journal of Xi’an University of Science and Technology, 2017, 37（6）: 892.
[30]	Huda A S N, Taib S. Application of infrared thermography for predictive/preventive maintenance of ther-maldefect in electrical equipment[J]. Applied Thermal Engineering, 2013, 61（2）: 220-227.
[31]	Jadin M S, Taib S. Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography[J]. Infrared Physics and Technology, 2012, 55（4）: 236-245.
[32]	王星.基于视觉的煤矿井下带式输送机异常状态监测方法研究[D].太原：太原科技大学，2017.
[33]	赵文博.井下胶带输送机的智能视频监测方法研究[D].西安：西安科技大学，2014.
[34]	Fromme CC, Stager DJ, Pilarski TE, et al. Conveyor belt inspection system and method: US6988610[P]. 2006-01-24.
[35]	何倩.基于视觉技术的井下胶带运输机运动监测方法研究[D].西安：西安科技大学，2012.
[36]	Zhu Aichun, Hua Gang, Wang Yongxing. The research on the detection method of belt deviation by video in coal mine[C]//2011 International Conference on Mechatronic Science, Electric Engineering and Computer（MEC）. IEEE, 2011: 430-433.
[37]	祁隽燕，谭超，李浩.基于数字图像处理的皮带纵向撕裂视觉识别[J].煤炭技术，2006，25（11）：15-17. QI Junyan, TAN Chao, LI Hao. Vision identification for longitudinal rip of steel-cord belt based on digital image process[J]. Coal Technology, 2006, 25（11）: 15-17.
[38]	祁隽燕，闫海峰，谭超，等.基于LabVIEW的胶带撕裂机器视觉检测系统研究[J].煤炭工程，2009（9）：123-125. QI Junyan,YAN Haifeng, TAN Chao. Machine vision inspection system of belt tearing base on Labview[J]. Coal Engineering, 2009（9）: 123-125.
[39]	Guijun Chen, Xueying Zhang, Zizhong John Wang, et al. Robust support vector data description for outlier detection with noise or uncertain data[J]. Knowledge-Based Systems, 2015, 90（9）:129-137.
[40]	Yi Yang, Chengcheng Hou, Tiezhu Qiao, et al. Longitudinal tear early-warning method for conveyor belt based on infrared vision[J]. Measurement, 2019, 147:106817.
[41]	Ruiyun Yang, Tiezhu Qiao, Yusong Pang, et al. Infrared Spectrum Analysis Method for Detection and Early Warning of Longitudinal Tear of Mine Conveyor Belt[J]. Measurement, 2020, 165（12）:107856.
[42]	杨洋.基于计算机视觉的输送带纵向撕裂检测算法研究与系统实现[D].太原：太原理工大学，2015.
[43]	施山菁.基于GPRS的带式输送机无线监测系统的研究[D].南京：南京林业大学，2013.
[44]	武斌.基于物联网的胶带输送机状态监测及寿命管理系统开发[D].太原：太原理工大学，2016.
[45]	张长森，潘志勇，王玉琨.基于Web的矿井主运输带式输送机在线监测及故障诊断系统[J].矿山机械，2009（11）：78. ZHANG Changsen, PAN Zhiyong, WANG Yukun Web based on-line monitoring and fault diagnosis system design for the main transport of mine conveyor[J]. Mining & Processing Equipment, 2009（11）: 78.
[46]	刘露露.基于CAN总线的煤矿带式输送机监测系统的设计方案[J].煤矿机电，2017（1）：74-76. LIU Lulu. Design of monitoring system on belt conveyorin coal mine based on CAN bus[J]. Colliery Mechanical & Electrical Technology, 2017（1）: 74-76.
[47]	李宏伟，李璐，曲兵妮，等.基于RS485和CAN总线的带式输送机监控系统设计[J].煤炭工程，2017， 49（7）：18-21. LI Hongwei, LI Lu, QU Bingni, et al. Design of belt conveyor monitoring system based on RS485 and CAN bus[J].Coal Engineering, 2017, 49（7）: 18-21.
[48]	邓军，肖旸，陈晓坤，等.矿井火灾多源信息融合预警方法的研究[J].采矿与安全工程学报，2011，28（4）：638-643. DENG Jun, XIAO Yang, CHEN Xiaokun, et al. Study on early warning method of multi-source information fusion for coal mine fire[J]. Journal of Mining & Safety Engineering, 2011, 28（4）: 638-643.
[49]	杨祥.矿用胶带输送机监测监控及故障诊断系统的开发[D].太原：太原理工大学，2019.
[50]	丁永生.计算智能:理论、技术与应用[M].北京：科学出版社，2004.
[51]	Yuanbin Wang, Yujing Wang, Langfei Dang. Video detection of foreign objects on the surface of belt conveyor underground coal mine based on improved SSD[J]. Journal of Ambient Intelligence and Humanized Computing, 2020. https://doi.org/10.1007/s12652-020-02495-w
[52]	樊荣，侯媛彬，张代，等.基于神经网络的带式输送机火灾预警算法[J].工矿自动化，2012（9）：70-74. FAN Rong, HOU Yuanbin, ZHANG Dai, et al. Fire pre-warning algorithm of belt conveyor based on neural network[J]. Industry and Mine Automation, 2012（9）: 70-74.
[53]	张美金，田宇驰，方志朋.矿井主运输系统火灾预测的RS-SVM模型[J].测控技术，2018，37（9）：29. ZHANG Meijin, TIAN Yuchi, FANG Zhipeng. RS-SVM model for fire prediction of mine transportation system[J]. Measurement & Control Technology, 2018, 37（9）: 29-32.
[54]	Xiao-li Hao, Huan Liang. A multi-class support vector machine real-time detection system for surface damage of conveyor belts based on visual saliency[J]. Measurement, 2019, 146: 125-132.
[55]	韩涛，黄友锐，张立志，等.基于图像识别的带式输送机输煤量和跑偏检测方法[J].工矿自动化，2020， 46（4）：17-22. HAN Tao, HUANG Yourui, ZHANG Lizhi, et al. Detection method of coal quantity and deviation of belt conveyor based on image recognition[J]. Industry and Mine Automation, 2020, 46（4）: 17-22.

Cited By

Cited by

Periodical cited type(21)

1.	耿哲，张德胜. 煤矿井下区域防灭火系统的设计. 矿山机械. 2025(03): 50-55 .
2.	邓军，李鑫，王凯，王伟峰，闫军，汤宗情，康付如，任帅京. 矿井火灾智能监测预警技术近20年研究进展及展望. 煤炭科学技术. 2024(01): 154-177 .
3.	段佳磊，梁运涛，贾宝山，孙勇，王睿德，罗奕杭，崔鑫峰. 阻燃输送带火灾早期温度变化与烟气成分研究. 矿业科学学报. 2024(02): 135-143 .
4.	李振囡，陆伟. 矿井输送带在不同气氛下的热解特性及动力学研究. 山西焦煤科技. 2024(03): 10-13 .
5.	王伟峰，杨博，甘梅，任立峰，康付如，刘韩飞. 基于PSO-SVM的矿井输送带火灾危险程度预测模型研究. 煤炭技术. 2024(05): 212-216 .
6.	郝守礼，乔燕军，范科，赵文韬，丁洒. 光伏发电区红外热成像火灾预警系统研究. 信息与电脑(理论版). 2024(05): 59-61 .
7.	王振兴，周廷斌，王伟峰，康付如，任晓伟. 矿用胶带火灾危险性评价研究. 煤炭工程. 2024(04): 144-149 .
8.	韩宝虎，张磊，杨坤，孙魁元，伯儿波特. 分布式光纤声学检测技术在煤矿带式输送机监测中的应用. 煤炭技术. 2024(07): 266-269 .
9.	梁文伟. DSJ80/40/2×75型带式输送机状态监控与故障诊断系统设计研究. 山东煤炭科技. 2024(06): 84-88 .
10.	王博强. 基于多模态温度探测的输煤廊道火灾极早期发现系统开发. 工业控制计算机. 2024(07): 6-8 .
11.	唐松，田波. 基于多传感信息融合技术的矿山机电设备运行状态监测方法. 矿业装备. 2024(05): 147-149 .
12.	李振囡，陆伟，卓辉，郑欣，李宇旋. 矿井输送带与煤粉混合热解特性及动力学研究. 煤炭技术. 2024(08): 169-173 .
13.	段石，郑旋，赵慧. 转龙湾煤矿主斜井运输机火灾预警及消防系统设计. 内蒙古煤炭经济. 2024(16): 16-18 .
14.	迟焕磊，宋振铎，单鹏. 煤矿智能化工作面的安全监测与预警系统深入探究. 张江科技评论. 2024(04): 117-119 .
15.	音勇. 煤矿井下输送机胶带燃烧特性实验研究. 煤炭科技. 2024(06): 51-56 .
16.	罗府勤，方芳. 不同物料带式输送系统的设计与改进研究——以制糖企业甘蔗输送设备为例. 造纸装备及材料. 2023(01): 62-64 .
17.	李希腾，秦宏楠，陈冠达，钱洪伟，李信. 煤矿企业智慧应急能力评价模型及应用研究. 煤矿安全. 2023(11): 233-239 . 本站查看
18.	贺杰，王标，王瑞君. 基于融合多传感器的煤矿带式输送机视频巡检系统设计与应用. 煤矿机械. 2023(12): 148-151 .
19.	许伟健，张德胜，黄增波. 基于双波长光电感烟的煤矿火灾烟雾监测技术. 煤矿安全. 2023(12): 204-212 . 本站查看
20.	娄树宏. 氮气防灭火在3104工作面采空区的技术应用. 内蒙古煤炭经济. 2022(21): 90-92 .
21.	于世勇. 煤矿用空压机智能群控节能控制系统的应用研究. 内蒙古煤炭经济. 2022(21): 21-23 .

Other cited types(4)

Get Citation

PDF

XML

Article views (76) PDF downloads (38) Cited by(25)

Turn off MathJax

Article Contents

Abstract

References

Research progress on intelligent monitoring and early warning technology of fire risk in coal mine belt conveyor transportation

Abstract

References

Cited by

Periodical cited type(21)

Other cited types(4)

Catalog

Export File

Citation

Format

Content