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遥感技术与应用  2019, Vol. 34 Issue (2): 263-268    DOI: 10.11873/j.issn.1004-0323.2019.2.0263
LiDAR专栏     
PPP技术与机载激光雷达在电力线巡检中的应用研究
杜跃飞1,2,3,刘正军3,冯天文1,2
(1.兰州交通大学 测绘与地理信息学院,甘肃 兰州 730070;
2.兰州交通大学 甘肃省地理国情监测工程实验室,甘肃 兰州 30070;
3.中国测绘科学研究院摄影测量与遥感研究所,北京 00830)
Application of PPP Technology and Airborne Lidar in Power Line Inspection
Du Yuefei1,2,3,Liu Zhengjun3,Feng Tianwen1,2
(1.Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070,China;
2.Gansu Provincial Engineering Laboratory for National Geographic State Monitoring,LanzhouJiaotong University,Lanzhou 730070,China;
3.Institute of Photogrammetry and Remote Sensing,Chinese Academy of Surveying andMapping,Beijing 100830,China)
 全文: PDF(4092 KB)  
摘要: 通过无人机电力线巡检试验,提出应用GPS、GLONASS和BDS多源融合的PPP技术并验证其生成的POS数据和三维点云数据应用于高压电力线巡检的可行性。采用不同策略的POS数据融合与解算,分析了基站差分POS数据与单GPS系统下的POS数据、GPS、GLONASS和BDS多系统融合下的POS数据精度;分别用不同策略的POS数据生成三维点云,并统计分析与基站差分点云数据的偏差距离和分布情况。研究发现:单GPS所生成的点云数据,距离偏差较大在20~40 cm左右,且分布不均匀,偏差距离波动较大,不能满足电力线精细巡检的要求;多源融合的PPP技术所生成的点云数据,与基站差分下的点云数据距离偏差在X方向10 cm,Y方向6 cm,Z方向为4 cm,点云数据分布均匀,稳定,基本满足电力线巡检要求,且点云数据也可用于电力线的精细巡检。
Abstract: Through the power line test,this paper presents the feasibility of applying the PPP technology of GPS,GLONASS and BDS multi-source fusion to verify the application of the generated POS data and 3D point cloud data to the high voltage power line inspection.The POS data fusion and calculation of different strategies are used to analyze the POS data accuracy of the POS data,GPS,GLONASS and BDS multi-systems under the base station differential POS data and the single GPS system.The 3D point cloud is generated by the POS data of different strategies,and the deviation distance and distribution of differential point cloud data are statistically analyzed.Finally,it is concluded that the point cloud data generated by the single GPS is about 20-40 cm,and the distribution is not uniform and the deviation distance fluctuates greatly.It can not meet the requirement of the fine inspection of the power line.The point cloud data generated by the PPP technology of multi-source fusion and the distance deviation from the point cloud data under the base station difference are 10 cm in the direction of X,The direction of Y is 6 cm and the direction of Z is 4 cm.The distribution of point cloud data is uniform and stable,which basically meets the requirements of the power line inspection,and the point cloud data can also be used for the fine inspection of the power line.
Key words: Precision point positioning    High voltage transmission line    GPS    Point cloud    Multi-source data    Unmanned helicopter
收稿日期: 2018-06-25 出版日期: 2019-05-10
ZTFLH:  P237  
基金资助: 国家重点研发计划项目“全天时主动式高光谱激光雷达成像技术”(2018YFB0504500),国家电网公司科技项目“输电通道全景测量与动态复原仿真技术研究及应用”(5211DS17002H)资助。
作者简介: 杜跃飞(1991-),男,河南汝州人,硕士研究生,主要从事机载激光雷达算法与数据处理研究。E-mail:1213635741@qq.com。
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引用本文:

杜跃飞, 刘正军, 冯天文. PPP技术与机载激光雷达在电力线巡检中的应用研究[J]. 遥感技术与应用, 2019, 34(2): 263-268.

Du Yuefei, Liu Zhengjun, Feng Tianwen. Application of PPP Technology and Airborne Lidar in Power Line Inspection. Remote Sensing Technology and Application, 2019, 34(2): 263-268.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.2.0263        http://www.rsta.ac.cn/CN/Y2019/V34/I2/263

[1]Baltsavias E P.Airborne Laser Scanning:Existing Systems and Firms and Other Resources[J].ISPRS Journal of Photogrammetry and Remote Sensing,1999,54(2-3):164-198.] [2]Shan J,Toth C K.Topographic Laser Ranging and Scanning:Principles and Processing.Scanning-Principles and Processing[M].Boca Raton:Boca CRS Press,2008. [3]Yang Feng,Xu Zujian.Application of the LiDAR Technology on Operation and Maintenance of Power Transmission Lines[J].Southern Power System Technology,2009,3(2):62-64.[阳锋,徐祖舰.三维激光雷达技术在输电线路运行与维护的应用[J].南方电网技术,2009,3(2):62-64.] [4]Liu Zhengjun,Peng Xiangyang,Guo Xiaolong,et al.Large-scale UAV Power Line Inspection Data Acquisition and Processing Technology[M].Beijing:China Electric Power Press.2015.[刘正军,彭向阳,郭小龙,等.大型无人机电力线路巡检数据采集与处理技术[M].北京:中国电力出版社,2015.] [5]Yuan Xiuxiao,Fu Jianhong,Lou Yidong.GPS-Supported Aerotriangulation based on GPS Precise Point Positioning[J].Acta Geodaetica et Cartographica Sinica,2007,36(3):251-255.[袁修孝,付建红,楼益栋.基于精密单点定位技术的GPS辅助空中三角测量[J].测绘学报,2007,36(3):251-255.] [6]Wang Li,Zhang Qin,Huang Guanwen,et al.Experiment Results and Analysis of Landslide Monitoring by Using GPS PPP Technology[J].Rock and Soil Mechanics 2014,35(7):2118-2124.[王利,张勤,黄观文,等.GPS PPP技术用于滑坡监测的试验与结果分析[J].岩土力学,2014,35(7):2118-2124.] [7]Zhu Yongxing,Feng Laiping,Jia Xiaolin,et al.The PPP Precision Analysis based on BDS Regional Navigation System[J].Acta Geodaetica et Cartographica Sinica.2015,44(4):377-383.[朱永兴,冯来平,贾小林,等.北斗区域导航系统的PPP精度分析[J].测绘学报,2015,44(4):377-383.] [8]Zhang Xiaohong,Guo Fei,Li Xingxing,et al.Study on Precise Point Positioning based on Combined GPS and GLONASS[J].Geomatics and Information Science of Wuhan University,2010,35(1):9-12.[张小红,郭斐,李星星,等.GPS/GLONASS组合精密单点定位研究[J].武汉大学学报·信息科学版,2010,35(1):9-12.] [9]Meng Xiangguang,Guo Jiming.GPS-GLONASS and Their Combined Precise Point Positioning[J].Geomatics and Information Science of Wuhan University,2010,35(12):1409-1413.[孟祥广,郭际明.GPS/GLONASS及其组合精密单点定位研究[J].武汉大学学报·信息科学版,2010,35(12):1409-1413.] [10]Wang Liang,Li Zishen,Yuan Hong,et al.Validation and Analysis of the Performance of Dual-Frequency Single-Epoch BDS/GPS/GLONASS Relative Positioning[J].Chinese Science Bulletin,2015,60(9):857-868.[汪亮,李子申,袁洪,等.BDS/GPS/GLONASS组合的双频单历元相对定位性能对比分析[J].科学通报,2015,60(9):857-868.] [11]Ren Xiaodong,Zhang Keke,Li Xingxing,et al.Precise Point Positioning with Multi-constellation Satellite Systems:Beidou、Galileo、GLONASS、GPS[J].Acta Geodaetica et Cartographica Sinica,2015,44(12):1307-1313.[任晓东,张柯柯,李星星,等.Beidou、Galileo、GLONASS、GPS多系统融合精密单点[J].测绘学报,2015,44(12):1307-1313.] [12]Elliott D.Kaplan,Christopher J.Hegarty.Understanding GPS:Principles and Applications[M].Beijing:Publishing House of Electronics Industry,2007.[寇艳红译.GPS原理与应用[M].北京:电子工业出版社,2007.] [13]Li Hefeng,Dang Yamin,Bei Jinzhong,et al.Research on Spatio Tempora Unification of BDS/GPS/GLONASS Multi-Mode Fusion Navigation and Positioning[J].Journal of Geodesy and Geodynamics,2013,33(4):73-78.[李鹤峰,党亚民,秘金钟,等.BDS与GPS、GLONASS多模融合导航定位时空统一[J].大地测量与地球动力学,2013,33(4):73-78.]
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