Abstract
Because the transmission line spans a wide area and the environment is complex, the current distance measuring equipment can not meet the requirements of the smart grid construction for the distance measuring accuracy of the hidden trouble of the transmission line, therefore, this paper proposes a transmission line fault location method based on monocular image and lidar information fusion. The 3D data of the hidden target can be obtained by the method of the joint modeling and ranging of the target detection of the 2D monocular image and the 3D laser point cloud re-projection, and the precise measurement of the hidden target and the clearance distance between the hidden target and the traverse can be realized, according to the type of hidden danger and the distribution of target, a point cloud updating strategy is formulated, and the relative error of clearance range is less than 2%, and the detection of lidar is real-time, it is proved that the proposed method can meet the precision requirement of hidden fault location of transmission line, and is helpful to improve the intelligence level of transmission line operation and maintenance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Cheng, Z.Y., Tang, M.J., Li, X.J., et al.: Fault location method of distribution line based on two-terminal electrical power quantities. Electr. Meas. Instrum. 55(8), 46–50, 57(2018)
Hou, Y.H., Yin, Y.Q., Cui, G.X., et al.: A fault location method of transmission line based on laser ranging and multi-feature joint judgement. Power Syst. Clean Energy 37(07), 73–78 (2021)
Zhang, J., Wang, J.Y., Song, R., et al.: Research on efficient detection technology of transmission line abnormal target based on edge intelligence. Power Syst. Technol. 46(05), 1652–1661 (2022)
Song, W., Zhu, M.F., Zhang, M.H., et al.: A review of monocular depth estimation techniques based on deep learning. J. Image Graph. 27(02), 0292–0328 (2022)
Shao, G.W., Liu, Z., Fu, J., et al.: Research progress in unmanned aerial vehicle inspection technology on overhead transmission lines. High Volt. Eng. 46(01), 14–22 (2020)
Wang, H.P., **a, S.B., Tan, H.W., et al.: The key technology of airborne laser point cloud data processing in power line inspection. Geosp. Inf. 13(05), 59–62 (2015)
Du, C.Q., Chen, B., Yu, Y.Z., et al.: Assessment of the sag of transmission line based on 3D model comparison. Power Syst. Clean Energy 37(06), 35–42 (2021)
Jia, S.X., Xu, Y., Gao, Q., et al.: Review of common problems and solutions of camera calibration. In: Proceedings of 2019 7th International Conference on Machinery, Materials and Computing Technology, pp. 642–647 (2019)
Ni, Q.D., Li, D., Chen, Y., et al.: Visual positioning algorithm based on micro assembly lin. In: Proceedings of 2020 4th International Conference on Electrical, Automation and Mechanical Engineering, pp. 168–174 (2020)
Lian, Y.X., Guo, Y.N., Chang, J., et al.: Permanent magnet synchronous motor control of electromechanical actuator based on parameter self-tuning method. In: Proceedings of the 33rd Chinese Control and Decision Conference, pp. 353–358 (2021)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Cai, F. et al. (2023). Transmission Line Fault Location Method Based on Monocular Image and Lidar Information Fusion. In: You, P., Li, H., Chen, Z. (eds) Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022). ICIVIS 2022. Lecture Notes in Electrical Engineering, vol 1019. Springer, Singapore. https://doi.org/10.1007/978-981-99-0923-0_47
Download citation
DOI: https://doi.org/10.1007/978-981-99-0923-0_47
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-0922-3
Online ISBN: 978-981-99-0923-0
eBook Packages: EngineeringEngineering (R0)