综掘工作面远程可视化控制关键技术研究
|
摘要
针对综掘工作面智能化、信息化水平滞后的现状,在借鉴综采工作面智能化技术体系的基础上,提出综掘工作面远程可视化控制方法。通过分析综掘工作面作业需求,提出各单机设备、工作面成套装备必需的智能化信息技术支撑。阐述了成套设备协同控制、智能截割、智能锚护、智能运输、视频监控、故障诊断及预测6项关键技术。对现有综掘装备情况及技术可行性进行了详细分析,明确了综掘工作面远程可视化控制的技术路线。同时提出在辅料运输、环境安全监测等方面,需要因地制宜进行工艺革新,进而实现智能化系统集成的问题。在现阶段,通过远程可视化控制技术体系,实现了综掘工作面减人增效、安全作业、沉淀生产数据的目标。
Based on the present status of the intelligent and informational level of fully-mechanized heading face,the remote visualization control of fully-mechanized heading face is proposed on the basis of the intelligent technology system of fully mechanized heading face.By analyzing the working requirements of comprehensive fully-mechanized heading face,the intelligent information technology support necessary for each stand-alone equipment and working face equipment is proposed.The six key technologies of collaborative control,intelligent cutting,intelligent anchor protection,intelligent transportation,video surveillance,fault diagnosis and prediction were described. The present status and technical feasibility of fully-mechanized equipment were analyzed in detail,and the technical route of remote visual control of fully-mechanized heading face was clarified.At the same time,it is proposed that in the aspects of auxiliary material transportation and environmental safety monitoring,it is necessary to carry out process innovation according to local conditions,and then realize the problem of intelligent system integration.At this stage,through the remote visual control technology system,the goal of reducing the efficiency of people,increasing safety,and precipitating production data is realized.
Based on the present status of the intelligent and informational level of fully-mechanized heading face,the remote visualization control of fully-mechanized heading face is proposed on the basis of the intelligent technology system of fully mechanized heading face.By analyzing the working requirements of comprehensive fully-mechanized heading face,the intelligent information technology support necessary for each stand-alone equipment and working face equipment is proposed.The six key technologies of collaborative control,intelligent cutting,intelligent anchor protection,intelligent transportation,video surveillance,fault diagnosis and prediction were described. The present status and technical feasibility of fully-mechanized equipment were analyzed in detail,and the technical route of remote visual control of fully-mechanized heading face was clarified.At the same time,it is proposed that in the aspects of auxiliary material transportation and environmental safety monitoring,it is necessary to carry out process innovation according to local conditions,and then realize the problem of intelligent system integration.At this stage,through the remote visual control technology system,the goal of reducing the efficiency of people,increasing safety,and precipitating production data is realized.
引文
[1]张科学.综掘工作面智能化开采技术研究[J].煤炭科学技术,2017,45(7):106-111.ZHANG Kexue.Study on intelligent mining technology of fullymechanized heading face[J].Coal Science and Technology,2017,45(7):106-111.
[2]王国法,张德生.煤炭智能化综采技术创新实践与发展展望[J].中国矿业大学学报,2018,47(3):459-467.WANG Guofa,ZHANG Desheng.Innovation practice and development prospect of intelligent fully mechanized technology for coal mining[J].Journal of China University of Mining&Technology,2018,47(3):459-467.
[3]王国法,王虹,任怀伟,等.智慧煤矿2025情景目标和发展路径[J].煤炭学报,2018,43(2):295-305.WANG Guofa,WANG Hong,REN Huaiwei,et al.2025 scenarios and development path of intelligent coal mine[J].Journal of China Coal Society,2018,43(2):295-305.
[4]RALSTON Jonathon R D,HARGRAVE Chad,HAINSWORTH David.Sensing for advancing mining automation capability:a review of underground automation technology development[J].International Journal of Mining Science and Technology,2014,24(5):305-310.
[5]郑兴,张高峰,王红旗.煤矿灾害救援双级式信息探测机器人系统研制[J].煤炭科学技术,2017,45(5):58-64,135.ZHENG Xing,ZHANG Gaofeng,WANG Hongqi.Research and development on robot system of mine disasterrescue second grade information detection[J].Coal Science and Technology,2017,45(5):58-64,135.
[6]王金华,黄乐亭,李首滨,等.综采工作面智能化技术与装备的发展[J].煤炭学报,2014,39(8):1418-1423.WANG Jinhua,HUANG Leting,LI Shoubin,et al.Development of intelligent technology and equipment in fully-mechanized coal mining face[J].Journal of China Coal Society,2014,39(8):1418-1423.
[7]陈晓晶,何敏.智慧矿山建设架构体系及其关键技术[J].煤炭科学技术,2018,46(2):208-212,236.CHEN Xiaojing,HE Min.Framework system and key technology of intelligent mine construction[J].Coal Science and Technology,2018,46(2):208-212,236.
[8]何敏.智慧矿山重要特征与实现途径[J].工矿自动化,2018,44(3):31-35.HE Min.Important characteristics and realization ways of wisdom mine[J].Industry and Mine Automation,2018,44(3):31-35.
[9]孙江.综采工作面远程控制采煤技术探讨[J].中国矿山工程,2017,46(6):62-65,77.SUN Jiang.Discussion on long-range control coal mining on fully mechanized working face[J].China Mine Engineering,2017,46(6):62-65.
[10]黄曾华,南柄飞,张科学,冯银辉.基于Ethernet/IP综采机器人一体化智能控制平台设计[J].煤炭科学技术,2017,45(5):9-15.HUANG Zenghua,NAN Bingfei,ZHANG Kexue,Feng Yinhui.Design on intelligent control platform of mechanized mining robot based on Ethernet/IP[J].Coal Science and Technology,2017,45(5):9-15.
[11]李刚,牛磊,李文龙.煤矿硬岩巷道快速掘进技术研究[J].煤炭科学技术,2018,46(11):13-20.LI Gang,NIU Lei,LI Wenlong.Study on rapid excavation technology for hard rock roadway in coal mine[J].Coal Science and Technology,2018,46(11):13-20.
[12]张东宝.煤巷智能快速掘进技术发展现状与关键技术[J].煤炭工程,2018,50(5):56-59.ZHANG Dongbao.Development status and key technology of intelligent rapid driving technology in coal seam roadway[J].Coal Engineering,2018,50(5):56-59.
[13]呼守信.高效快速掘进系统的协同控制[J].工矿自动化,2017.43(4):86-88.HU Shouxin.Cooperative control of high-efficient and rapid excavation system[J].Industry and Mine Automation,2017,43(4):86-88.
[14]曹飞飞.岩巷快速掘进优化设计及应用[D].邯郸:河北工程大学,2014.
[15]马睿.巷道快速掘进空顶区顶板破坏机理及稳定性控制[D].徐州:中国矿业大学,2016.
[16]王伟,田慕琴,闫琳,等.多神经网络与证据理论相融合的掘进机动载荷识别方法[J].煤炭技术,2018,37(4):228-231.WANG Wei,TIAN Muqin,YAN Lin,et al.Dynamic load identification method of rock roadheader using multineural network and evidence theory[J].Coal Technology,2018,37(4):228-231.
[17]王伟,田慕琴,宋建成,等.基于小波包神经网络的岩巷掘进机动载荷识别方法[J].煤矿机械,2015,36(3):238-241.WANG Wei,TIAN Muqin,SONG Jiancheng,et al.Dynamic load identification method of rock roadheader based on wavelet packet and neural network[J].Coal Mine Machinery,2015,36(3):238-241.
[18]何洋,李晓豁.纵轴式掘进机截割头随机截割载荷识别方法研究[J].武汉科技大学学报,2017,40(2):138-143.HE Yang,LI Xiaohuo.Identification of random cutting load on cutting head of longitudinal roadheader[J].Journal of Wuhan University of Science and Technology,2017,40(2):138-143.
[19]刘旭南.掘进机动态可靠性及其关键技术研究[D].阜新:辽宁工程技术大学,2014.
[20]袁冯丹.全断面掘进机故障预测与健康管理系统研究[D].石家庄:石家庄铁道大学,2017.
[21]左庆林.盾构机关键设备状态监测与故障诊断究[D].石家庄:石家庄铁道大学,2014.
[2]王国法,张德生.煤炭智能化综采技术创新实践与发展展望[J].中国矿业大学学报,2018,47(3):459-467.WANG Guofa,ZHANG Desheng.Innovation practice and development prospect of intelligent fully mechanized technology for coal mining[J].Journal of China University of Mining&Technology,2018,47(3):459-467.
[3]王国法,王虹,任怀伟,等.智慧煤矿2025情景目标和发展路径[J].煤炭学报,2018,43(2):295-305.WANG Guofa,WANG Hong,REN Huaiwei,et al.2025 scenarios and development path of intelligent coal mine[J].Journal of China Coal Society,2018,43(2):295-305.
[4]RALSTON Jonathon R D,HARGRAVE Chad,HAINSWORTH David.Sensing for advancing mining automation capability:a review of underground automation technology development[J].International Journal of Mining Science and Technology,2014,24(5):305-310.
[5]郑兴,张高峰,王红旗.煤矿灾害救援双级式信息探测机器人系统研制[J].煤炭科学技术,2017,45(5):58-64,135.ZHENG Xing,ZHANG Gaofeng,WANG Hongqi.Research and development on robot system of mine disasterrescue second grade information detection[J].Coal Science and Technology,2017,45(5):58-64,135.
[6]王金华,黄乐亭,李首滨,等.综采工作面智能化技术与装备的发展[J].煤炭学报,2014,39(8):1418-1423.WANG Jinhua,HUANG Leting,LI Shoubin,et al.Development of intelligent technology and equipment in fully-mechanized coal mining face[J].Journal of China Coal Society,2014,39(8):1418-1423.
[7]陈晓晶,何敏.智慧矿山建设架构体系及其关键技术[J].煤炭科学技术,2018,46(2):208-212,236.CHEN Xiaojing,HE Min.Framework system and key technology of intelligent mine construction[J].Coal Science and Technology,2018,46(2):208-212,236.
[8]何敏.智慧矿山重要特征与实现途径[J].工矿自动化,2018,44(3):31-35.HE Min.Important characteristics and realization ways of wisdom mine[J].Industry and Mine Automation,2018,44(3):31-35.
[9]孙江.综采工作面远程控制采煤技术探讨[J].中国矿山工程,2017,46(6):62-65,77.SUN Jiang.Discussion on long-range control coal mining on fully mechanized working face[J].China Mine Engineering,2017,46(6):62-65.
[10]黄曾华,南柄飞,张科学,冯银辉.基于Ethernet/IP综采机器人一体化智能控制平台设计[J].煤炭科学技术,2017,45(5):9-15.HUANG Zenghua,NAN Bingfei,ZHANG Kexue,Feng Yinhui.Design on intelligent control platform of mechanized mining robot based on Ethernet/IP[J].Coal Science and Technology,2017,45(5):9-15.
[11]李刚,牛磊,李文龙.煤矿硬岩巷道快速掘进技术研究[J].煤炭科学技术,2018,46(11):13-20.LI Gang,NIU Lei,LI Wenlong.Study on rapid excavation technology for hard rock roadway in coal mine[J].Coal Science and Technology,2018,46(11):13-20.
[12]张东宝.煤巷智能快速掘进技术发展现状与关键技术[J].煤炭工程,2018,50(5):56-59.ZHANG Dongbao.Development status and key technology of intelligent rapid driving technology in coal seam roadway[J].Coal Engineering,2018,50(5):56-59.
[13]呼守信.高效快速掘进系统的协同控制[J].工矿自动化,2017.43(4):86-88.HU Shouxin.Cooperative control of high-efficient and rapid excavation system[J].Industry and Mine Automation,2017,43(4):86-88.
[14]曹飞飞.岩巷快速掘进优化设计及应用[D].邯郸:河北工程大学,2014.
[15]马睿.巷道快速掘进空顶区顶板破坏机理及稳定性控制[D].徐州:中国矿业大学,2016.
[16]王伟,田慕琴,闫琳,等.多神经网络与证据理论相融合的掘进机动载荷识别方法[J].煤炭技术,2018,37(4):228-231.WANG Wei,TIAN Muqin,YAN Lin,et al.Dynamic load identification method of rock roadheader using multineural network and evidence theory[J].Coal Technology,2018,37(4):228-231.
[17]王伟,田慕琴,宋建成,等.基于小波包神经网络的岩巷掘进机动载荷识别方法[J].煤矿机械,2015,36(3):238-241.WANG Wei,TIAN Muqin,SONG Jiancheng,et al.Dynamic load identification method of rock roadheader based on wavelet packet and neural network[J].Coal Mine Machinery,2015,36(3):238-241.
[18]何洋,李晓豁.纵轴式掘进机截割头随机截割载荷识别方法研究[J].武汉科技大学学报,2017,40(2):138-143.HE Yang,LI Xiaohuo.Identification of random cutting load on cutting head of longitudinal roadheader[J].Journal of Wuhan University of Science and Technology,2017,40(2):138-143.
[19]刘旭南.掘进机动态可靠性及其关键技术研究[D].阜新:辽宁工程技术大学,2014.
[20]袁冯丹.全断面掘进机故障预测与健康管理系统研究[D].石家庄:石家庄铁道大学,2017.
[21]左庆林.盾构机关键设备状态监测与故障诊断究[D].石家庄:石家庄铁道大学,2014.