[1]李 健,徐 旭.基于无人机影像的煤场工程量监测分析[J].常州大学学报(自然科学版),2019,31(02):35-43.[doi:10.3969/j.issn.2095-0411.2019.02.005]
　LI Jian,XU Xu.Monitoring and Analysis Method of Yard Construction Quantity Based on UAV Image[J].Journal of Changzhou University(Natural Science Edition),2019,31(02):35-43.[doi:10.3969/j.issn.2095-0411.2019.02.005]
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基于无人机影像的煤场工程量监测分析()
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常州大学学报(自然科学版)[ISSN:2095-0411/CN:32-1822/N]

卷:
第31卷
期数:
2019年02期
页码:
35-43
栏目:
机械制造及其自动化
出版日期:
2019-03-28

文章信息/Info

Title:
Monitoring and Analysis Method of Yard Construction Quantity Based on UAV Image
文章编号:
2095-0411(2019)02-0035-09
作者:
李 健; 徐 旭
(常州大学 机械工程学院,江苏 常州 213164)
Author(s):
LI Jian;  XU Xu
(School of Mechanical Engineering, Changzhou University, Changzhou 213164, China)
关键词:
无人机;  煤场;  三维重建;  采挖量
Keywords:
unmanned aerial vehicle;  coal yard;  three dimensional reconstruction;  mining amount
分类号:
O 359
DOI:
10.3969/j.issn.2095-0411.2019.02.005
文献标志码:
A
摘要:
针对目前煤场采挖量体积计算效率低下及精度较低的问题, 提出了一种基于无人机影像序列的大型露天煤场采挖量计算方法。首先利用无人机获取煤场采挖前及采挖后的影像序列,采用多视图立体视觉重建算法对其进行三维重建,获取两个时期的煤堆三维点云信息。针对不同时期同一工程地点的点云数据,进行数据配准,然后对配准后数据中采挖区域进行精确定位和边界确定,并设计重建算法对采挖区域的点云进行网格重建,进而实现对采挖区域的分析、计算与监测。实验结果表明,该方法可准确定位采挖区域,精确计算不同区域采挖量,监测煤堆总体积变化。
Abstract:
Aiming at the problem of low efficiency and low accuracy in the volume calculation of coal yard excavation, a scheme for calculating the mining quantity of large open-pit coal yard based on UAV image sequence is proposed. First, the unmanned aerial vehicle is used to obtain the image sequences before and after mining the coal field, followed by the multi-view stereo vision reconstruction technique to reconstruct the three-dimensional point cloud of the two periods. Due to the point clouds acquired from the same engineering site in different periods, we can register the point clouds together and locate the mining area and the boundary precisely. Finally, the point cloud of the mining area can be reconstructed to a mesh model, so as to facilitate the analysis, calculation and monitoring of the mining area. The experimental results show that the presented scheme can accurately locate the mining area, calculate the mining volume, and monitor the overall volume change of coal stacking.

参考文献/References:


[1]林文. 断面数据土方量计算方法研究[J]. 地矿测绘,2010,26(1):39-41.
[2]陈爱梅,吴昊,吴北平,等.四种土方量计算方法的对比研究与应用[J]. 北京测绘, 2015(1):104-108.
[3]张婷婷,王铁良.土方量计算方法研究[J]. 安徽农业科学,2006,34(22):6047-6050.
[4]陈永锋, 吴晓茹, 原玉博.基于DTM的露天矿采剥工程量计算方法研究[J]. 金属矿山, 2010,39(12):15-17.
[5]LIU X, CHEN P, TONG X, et al. UAV-based low-altitude aerial photogrammetric application in mine areas measurement[C]// Second International Workshop on Earth Observation and Remote Sensing Applications. [S.l.]:IEEE, 2012:240-242.
[6]MCLEOD T, SAMSON C, LABRIE M, et al. Using video acquired from an unmanned aerial vehicle(uav)to measure fracture orientation in an open-pit mine[J]. Geomatica, 2013, 67(3):173-180.
[7]SNAVELY N, SIMON I, GOESELE M, et al. Scene reconstruction and visualization from community photo collections[J]. Proceedings of the IEEE, 2010, 98(8):1370-1390.
[8]周骏. 多视图图像三维重建若干关键技术研究[D].成都:电子科技大学, 2013.
[9]FUMKAWA Y,PONCE J.Accurate,dense,and robust multi-view stereopsis[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(8):1362-1376.
[10]许志华, 吴立新, 陈绍杰,等. 基于无人机影像的露天矿工程量监测分析方法[J]. 东北大学学报(自然科学版), 2016, 37(1):84-88.
[11]闫世博. 基于图像的三维重建及网格化算法研究[D].上海:上海交通大学, 2013.
[12]BESL P J, MCKAY N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2002, 14(2):239-256.
[13]郑鹏飞, 邹培玲, 赵菊娣, 等. 点云曲面空间网格化加密求交算法[J]. 浙江大学学报(工学版), 2018, 52(3): 605-612.
[14]KAZHDAN M, BOLITHO M, HOPPE H. Poisson surface reconstruction[C/OL]// Eurographics Symposium on Geometry Processing. Cagliar: [s.n.], 2006:61-70. https://dl.acm.org/citation.cfm?id=1281965.
[15]CURLESS B, LEVOY M. A volumetric method for building complex models from range images[C/OL]// Conference on Computer Graphics and Interactive Techniques. New York: ACM, 1996:303-312. https://graphics.stanford.edu/papers/volrange/.
[16]KAZHDAN M. Reconstruction of solid models from oriented point sets[C/OL]// Vienna: Eurographics Symposium on Geometry Processing. Vienna: Eurographics Association, 2005:73. https://dl.acm.org/citation.cfm?id=1281931.
[17]ZHANG C, CHEN T. Efficient feature extraction for 2D/3D objects in mesh representation[C/OL]//International Conference on Image Processing. Thessaloniki: IEEE, 2016:935-938. https://ieeexplore.ieee.org/abstract/document/958278.

备注/Memo

备注/Memo:
收稿日期:2018-12-09。
基金项目:国家自然科学基金资助项目(51501019)。
作者简介:李健(1963—),男,江苏常州人,硕士,副教授。E-mail:lj1231@cczu.edu.cn
更新日期/Last Update: 2019-03-30