Research on 3D reconstruction technology of large‐scale substation equipment based on NeRF

Abstract

Abstract The high‐quality 3D model is the key to digital twin and visualization. Here, the neural radiation field (NeRF) is applied to greatly improve the speed and accuracy of 3D reconstruction of large‐scale substation equipment. The incremental SFM algorithm is used to accurately position the camera in open scenes, and the frame extraction experiment indicates that the single angle increment should not be greater than 8°. The reconstruction test is carried out on the power transformer and high‐voltage experimental equipment following the circular shooting track for instant‐NGP (a variant of NeRF). Compared with the traditional 3D reconstruction method, the speed of reconstruction is accelerated by 23–55 times, and the fidelity is improved by 2–3 times. Also, the deployment scheme of NeRF in the digital twin technology of large‐scale substation equipment is proposed. The experimental results verify the effectiveness and feasibility of NeRF in practical application.

Keywords

• cloud computing
• image motion analysis
• image processing
• image reconstruction
• image sequences
• learning (artificial intelligence)