Abstract
The inspection procedure of Chinese high voltage power grid is mainly based on human inspection for many years. This is not only time-consuming and difficult, but the inspection results are also not objective and complete. Aiming at these problems, this paper gives a research method based on UAV-borne laser scanning. By taking the orthophotos of the power line corridor area and using the overlapping feature points of the image, the orientation elements of each photo are inversely calculated. According to the principle of aerial triangulation, the pixel matching algorithm is used to calculate the dense point cloud data of the survey area, and the power line point in the point cloud is selected to simulate the complete power line. By calculating the Euclidean distance between the power line and the power line protection area, the calculated result is compared with the power line safety specification to obtain information such as a tree barrier point or an early warning point. It can effectively identify many important defects such as wire-vegetation, wire-building, wire-crossing, etc., and greatly improve the quality and efficiency of the inspection process of existing high-voltage transmission lines.
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References
Kim, H.B., Sohn, G.: Point-based classification of power line corridor scene using random forests. Photogram. Eng. Remote Sens. 79(9), 821–833 (2013)
Lin, X., Zhang, J.: 3D power line reconstruction from airhornc LiDAR point cloud of overhead electric power transmission corridors. Acta Geodetica et Cartographzca Szrizca 45, 347–353 (2016)
Shao, T.: Mechanical Calculation of Overhead Electric Power Transmission Lines (Second Re-lease). China Electric Power Press, Beijing (2003)
Automatic recognition of defects on transmission lines from UAV-borne laser scanning data. Remote Sens. Inf. 32, 52–57 (2017)
Automatic extraction and reconstruction of bundle conductors from airborne LiDAR point clouds. Sci. Surv. Mapp. 43, 124–130 (2018)
Lhen, C., Mai, X., Song, S., et al.: Automatic power lines extraction method from airhornc LiDAR point cloud. Geomatics Inf. Sci. Wuhan Univ. 10(12), 1600–1605 (2015)
Lai, X., Dai, D., Zheng, M., et al.: A method for powerline 3D reconstruction based on LiDAR point cloud data. J. Remote Sens. 18(6), 1223–1229 (2014)
Ye, L., Liu, Q., Hu, Q.: Research of power line fitting and extraction techniques based on LiDAR point cloud data. Geomatics Spat. Inf. Technol. 33(5), 30–10 (2010)
Yu, J., Mu, C., Feng, Y., et al.: Powerlines extraction techniques from airborne LiDAR data. Geomatics Inf. Sci. Wuhum Univ. 36(11), 1275–1279 (2011)
Lai, X., Dai, D., Zheng, M., et al.: Power-line three-dimensional reconstruction for LiDAR point cloud data. J. Remote Sens. 18(6), 223–229 (2014)
Press, W.H., Flanncry, B.P., Teukolsky, S.A., et al.: Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, Cambridge (2007)
Acknowledgements
Implementation of innovation driven development capacity building special funds of Guangdong.
Academy of Sciences (2017GDASCX-0101, 2017GDASCX-0601).
Guangdong Innovative and Entrepreneurial Research Team Program (2016ZT06D336).
Guangzhou Science and Technology Program (201604016047, 201806010106).
Guangdong Science and Technology Program (2017B010117008).
Guangzhou Hydraulic Technological Innovation Project (MZSK-2016-01, SW-2018-01).
The National Natural Science Foundation of China (41401430).
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Yang, C., Li, Y., Zhou, X., Yang, J., Zhang, C., Liu, H. (2019). Research on 3D Reconstruction of Transmission Linesnd Identification of Hidden Dangers of Tree Barriers Based on Airborne Lidar Point Cloud. In: Xie, Y., Zhang, A., Liu, H., Feng, L. (eds) Geo-informatics in Sustainable Ecosystem and Society. GSES 2018. Communications in Computer and Information Science, vol 980. Springer, Singapore. https://doi.org/10.1007/978-981-13-7025-0_38
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DOI: https://doi.org/10.1007/978-981-13-7025-0_38
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