连续采煤机人员监测保护系统设计
|
摘要
针对连续采煤机后部输送机在工作过程中存在误伤行人的安全隐患,设计了一种基于红外热成像技术的连续采煤机人员监测保护系统。首先利用长波红外探头对连续采煤机后部输送机监测敏感区域进行监测,实时采集监测敏感区域内红外影像信息;然后利用微处理机对采集的红外影像信息进行实时性处理,并对行人进行检测,当检测到有行人进入到监测敏感区域时,在1s内快速判断行人信息,触发预警保护策略,当行人退出监测敏感区域后,预警保护机制自动停止,当行人越过监测敏感区域时,微处理机触发紧急停车控制策略,使连续采煤机后部输送机紧急停车,保护越界行人的安全。现场测试结果表明,该系统稳定、可靠,识别精度高,能够实现对连续采煤机后部输送机左前方1~2m范围内的行人进行有效监测,保证了连续采煤机附近人员的生命安全。
In view of potential safety hazards of accidentally injuring pedestrians during operation process of conveyor at the back of continuous shearer,apedestrian monitoring and protection system of continuous shearer based on infrared thermal imaging was designed.Firstly,long-wave infrared probe was used to monitor sensitive areas of the conveyor at the back of continuous shearer and real-timely collect infrared image information in the sensitive areas.Then,microprocessor was used to process the infrared image information,and pedestrians were detected;when pedestrians were detected entering the sensitive area,the pedestrian information would be rapidly judged by microprocessor within 1 s,meanwhile an early warning protection strategy would be triggered;when the pedestrians exited the sensitive area,the early warning protection mechanism would stop automatically;when the pedestrians passed over the sensitive area,at that time,an emergency stop control strategy would be triggered by microprocessor,so as to make the conveyor at the back of continuous shearer stop urgently to protect safety of crossing pedestrians.The site test results show that the system is stable and reliable with high recognitionaccuracy,and can effectively monitor pedestrians within the range of 1 to 2 meters on the front left area of the conveyor at the back of the continuous shearer,which effectively guaranteed life safety of pedestrians nearby the continuous shearer.
In view of potential safety hazards of accidentally injuring pedestrians during operation process of conveyor at the back of continuous shearer,apedestrian monitoring and protection system of continuous shearer based on infrared thermal imaging was designed.Firstly,long-wave infrared probe was used to monitor sensitive areas of the conveyor at the back of continuous shearer and real-timely collect infrared image information in the sensitive areas.Then,microprocessor was used to process the infrared image information,and pedestrians were detected;when pedestrians were detected entering the sensitive area,the pedestrian information would be rapidly judged by microprocessor within 1 s,meanwhile an early warning protection strategy would be triggered;when the pedestrians exited the sensitive area,the early warning protection mechanism would stop automatically;when the pedestrians passed over the sensitive area,at that time,an emergency stop control strategy would be triggered by microprocessor,so as to make the conveyor at the back of continuous shearer stop urgently to protect safety of crossing pedestrians.The site test results show that the system is stable and reliable with high recognitionaccuracy,and can effectively monitor pedestrians within the range of 1 to 2 meters on the front left area of the conveyor at the back of the continuous shearer,which effectively guaranteed life safety of pedestrians nearby the continuous shearer.
引文
[1]周树清,王平,王广斌.煤矿建设期间综掘机械化施工技术改造[J].煤炭工程,2011,43(增刊2):120-122.
[2]李翔,张北平,刘银根.人体感应红外技术在煤矿综掘机中的应用[J].煤炭科技,2009(2):98-99.
[3]陶明房,孙杰.掘进机人体保护装置研制与应用[J].煤矿开采,2009,14(6):63-64.
[4]包建军.煤矿井下装备接近探测方法研究[J].工矿自动化,2017,43(1):1-4.BAO Jianjun.Research on proximity detection method for machines in coal mine[J].Industry and Mine Automation,2017,43(1):1-4.
[5]赵岩,符如康,韩超.采煤工作面刮板运输机机头人体红外保护系统[J].山东煤炭科技,2015(2):151.ZHAO Yan,FU Rukang,HAN Chao.Human body infrared protection system of working face scraper conveyor head[J].Shandong Coal Science and Technology,2015(2):151.
[6]杨宇翔,高明煜,尹克,等.结合同场景立体图对的高质量深度图像重建[J].中国图象图形学报,2015,20(1):1-10.YANG Yuxiang,GAO Mingyu,YIN Ke,et al.Highquality depth map reconstruction combining stereo image pair[J].Journal of Image and Graphics,2015,20(1):1-10.
[7]谭志国,欧建平,张军,等.一种层析深度图像去噪算法[J].光学学报,2017,37(5):94-100.TAN Zhiguo,OU Jianping,ZHANG Jun,et al.A laminar denoising algorithm for depth image[J].Acta Optica Sinica,2017,37(5):94-100.
[8]董观利,宋春林.基于视频的矿井行人越界检测系统[J].工矿自动化,2017,43(2):29-34.DONG Guanli,SONG Chunlin.Underground pedestrian crossing detection system based on video[J].Industry and Mine Automation,2017,43(2):29-34.
[9]张桂梅,张松,储珺.一种新的基于局部轮廓特征的目标检测方法[J].自动化学报,2014,40(10):2346-2355.ZHANG Guimei,ZHANG Song,CHU Jun.A new object detection algorithm using local contour features[J].Acta Automatica Sinica,2014,40(10):2346-2355.
[10]蔡强,郝佳云,曹健,等.结合局部特征及全局特征的显著性检测[J].光学精密工程,2017,25(3):772-778.CAI Qiang,HAO Jiayun,CAO Jian,et al.Salient detection via local and global feature[J].Optics and Precision Engineering,2017,25(3):772-778.
[11]李响,谭南林,王天雷,等.复杂场景下基于局部运动补偿的目标检测[J].仪器仪表学报,2014,35(7):1555-1563.LI Xiang,TAN Nanlin,WANG Tianlei,et al.Object detection based on local motion compensation in complex scenes[J].Chinese Journal of Scientific Instrument,2014,35(7):1555-1563.
[12]常好丽,史忠科.基于单目视觉的运动行人检测与跟踪方法[J].交通运输工程学报,2006,6(2):55-59.CHANG Haoli,SHI Zhongke.Method of moving pedestrian detection and tracking based on monocular vision technology[J].Journal of Traffic and Transportation Engineering,2006,6(2):55-59.
[13]何元磊,王静荔,贾俊波,等.一种改进的高光谱遥感影像ACE目标检测算法[J].山东科技大学学报(自然科学版),2015,34(3):62-67.HE Yuanlei,WANG Jingli,JIA Junbo,et al.Improved ACE target detection algorithm for hyperspectral remote sensing images[J].Journal of Shandong University of Science and Technology(Natural Science),2015,34(3):62-67.
[14]付洋,宋焕生,陈艳,等.一种基于视频的道路行人检测方法[J].电视技术,2012,36(13):140-144.FU Yang,SONG Huansheng,CHEN Yan,et al.Method of detecting road pedestrian based on video[J].Video Engineering,2012,36(13):140-144.
[15]徐辉,贺耀宜.一种煤矿井下监控视频图像预处理方法[J].工矿自动化,2016,42(1):32-34.XU Hui,HE Yaoyi.An image preprocessing method for underground monitoring video[J].Industry and Mine Automation,2016,42(1):32-34.
[2]李翔,张北平,刘银根.人体感应红外技术在煤矿综掘机中的应用[J].煤炭科技,2009(2):98-99.
[3]陶明房,孙杰.掘进机人体保护装置研制与应用[J].煤矿开采,2009,14(6):63-64.
[4]包建军.煤矿井下装备接近探测方法研究[J].工矿自动化,2017,43(1):1-4.BAO Jianjun.Research on proximity detection method for machines in coal mine[J].Industry and Mine Automation,2017,43(1):1-4.
[5]赵岩,符如康,韩超.采煤工作面刮板运输机机头人体红外保护系统[J].山东煤炭科技,2015(2):151.ZHAO Yan,FU Rukang,HAN Chao.Human body infrared protection system of working face scraper conveyor head[J].Shandong Coal Science and Technology,2015(2):151.
[6]杨宇翔,高明煜,尹克,等.结合同场景立体图对的高质量深度图像重建[J].中国图象图形学报,2015,20(1):1-10.YANG Yuxiang,GAO Mingyu,YIN Ke,et al.Highquality depth map reconstruction combining stereo image pair[J].Journal of Image and Graphics,2015,20(1):1-10.
[7]谭志国,欧建平,张军,等.一种层析深度图像去噪算法[J].光学学报,2017,37(5):94-100.TAN Zhiguo,OU Jianping,ZHANG Jun,et al.A laminar denoising algorithm for depth image[J].Acta Optica Sinica,2017,37(5):94-100.
[8]董观利,宋春林.基于视频的矿井行人越界检测系统[J].工矿自动化,2017,43(2):29-34.DONG Guanli,SONG Chunlin.Underground pedestrian crossing detection system based on video[J].Industry and Mine Automation,2017,43(2):29-34.
[9]张桂梅,张松,储珺.一种新的基于局部轮廓特征的目标检测方法[J].自动化学报,2014,40(10):2346-2355.ZHANG Guimei,ZHANG Song,CHU Jun.A new object detection algorithm using local contour features[J].Acta Automatica Sinica,2014,40(10):2346-2355.
[10]蔡强,郝佳云,曹健,等.结合局部特征及全局特征的显著性检测[J].光学精密工程,2017,25(3):772-778.CAI Qiang,HAO Jiayun,CAO Jian,et al.Salient detection via local and global feature[J].Optics and Precision Engineering,2017,25(3):772-778.
[11]李响,谭南林,王天雷,等.复杂场景下基于局部运动补偿的目标检测[J].仪器仪表学报,2014,35(7):1555-1563.LI Xiang,TAN Nanlin,WANG Tianlei,et al.Object detection based on local motion compensation in complex scenes[J].Chinese Journal of Scientific Instrument,2014,35(7):1555-1563.
[12]常好丽,史忠科.基于单目视觉的运动行人检测与跟踪方法[J].交通运输工程学报,2006,6(2):55-59.CHANG Haoli,SHI Zhongke.Method of moving pedestrian detection and tracking based on monocular vision technology[J].Journal of Traffic and Transportation Engineering,2006,6(2):55-59.
[13]何元磊,王静荔,贾俊波,等.一种改进的高光谱遥感影像ACE目标检测算法[J].山东科技大学学报(自然科学版),2015,34(3):62-67.HE Yuanlei,WANG Jingli,JIA Junbo,et al.Improved ACE target detection algorithm for hyperspectral remote sensing images[J].Journal of Shandong University of Science and Technology(Natural Science),2015,34(3):62-67.
[14]付洋,宋焕生,陈艳,等.一种基于视频的道路行人检测方法[J].电视技术,2012,36(13):140-144.FU Yang,SONG Huansheng,CHEN Yan,et al.Method of detecting road pedestrian based on video[J].Video Engineering,2012,36(13):140-144.
[15]徐辉,贺耀宜.一种煤矿井下监控视频图像预处理方法[J].工矿自动化,2016,42(1):32-34.XU Hui,HE Yaoyi.An image preprocessing method for underground monitoring video[J].Industry and Mine Automation,2016,42(1):32-34.