Power grid fault location optimization based on point cloud inspection channel

Jianing Shang; An Chang; Wenjian Zheng; Mandi Cui; Yunhai Song

doi:10.1117/12.2635834

6 May 2022 Power grid fault location optimization based on point cloud inspection channel

Jianing Shang, An Chang, Wenjian Zheng, Mandi Cui, Yunhai Song

Proceedings Volume 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022); 1225602 (2022) https://doi.org/10.1117/12.2635834
Event: 2022 International Conference on Electronic Information Engineering, Big Data and Computer Technology, 2022, Sanya, China

Abstract

With the rapid expansion of power grid scale, for the mountainous areas with slow economic development, large-scale transmission lines have been exposed to the harsh environment for a long time, causing great damage to the transmission lines. In order to reduce the possibility of safety failure of transmission line, periodic inspection of transmission line is needed. Based on the power line extraction algorithm of LIDAR point cloud in the power line ecological corridor, a new multi split power line fitting method is proposed in this paper. The whole split conductor point cloud is fitted straight line in the XOY plane and catenary in the XOZ plane respectively. The curve equation obtained is used as the center line, and then the coordinates of each point relative to the center line are calculated. Experiments show that the algorithm proposed in this paper has obvious advantages in the extraction accuracy and adaptability of split sub conductors compared with the traditional algorithm. It can provide accurate positioning for the subsequent use of suspension points to simulate power lines to determine whether there are potential safety hazards, which provides technical support for the power grid construction.

Citation Download Citation

Jianing Shang, An Chang, Wenjian Zheng, Mandi Cui, and Yunhai Song "Power grid fault location optimization based on point cloud inspection channel", Proc. SPIE 12256, International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2022), 1225602 (6 May 2022); https://doi.org/10.1117/12.2635834

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