Real time dynamic fusion method of transmission and transformation project line and terrain 3D model based on GIM model
DOI:
https://doi.org/10.4108/ew.11602Keywords:
3D model, Dynamic fusion, Terrain, GIM model, Power transmission and transformationAbstract
INTRODUCTION: To address insufficient accuracy in transmission and transformation project line planning, difficulties in fusing line and terrain 3D models, and limited visualization in complex terrain, this paper investigates a real-time dynamic fusion approach for line–terrain 3D models based on the GIM model, aiming to support refined digital construction and management.
OBJECTIVES: The objective of this paper is to develop a real-time dynamic fusion method that (1)integrates multi-source geographic information into a unified 3D environment base, (2) enables intelligent multi-constraint route planning with automatic optimization and quantitative comparison of alternatives, and (3) supports efficient visualization for digital twin applications throughout the project lifecycle.
METHODS: A multi-source geographic information integrated 3D environment base is constructed, and a multi-constraint intelligent planning algorithm is established to perform automatic path optimization and multi-scheme quantitative evaluation. High-precision terrain is reconstructed by combining laser point cloud data and oblique photography, while a target registration strategy is adopted to unify coordinates between the GIM model and real terrain. A unified data engine together with hierarchical level-of-detail rendering is employed to realize real-time dynamic integration of construction resources, progress information, and 3D scenes.
RESULTS: Case studies demonstrate that the proposed method improves the rationality and economy of route planning, enables effective comparison among multiple planning schemes, significantly reduces ecological impact, and provides efficient real-time visualization and dynamic scene integration in complex terrain environments.
CONCLUSION: The proposed GIM-based real-time dynamic fusion framework enhances planning accuracy, model–terrain alignment, and visualization capability for power transmission and transformation projects, offering a reliable digital twin platform for fine-grained management across the entire project cycle and supporting the digital transformation of the industry.
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[1] Guo W, He P. Research on Life-cycle Control of Transmission and Transformation Engineering Based on 3D Intelligent Support Model [J]. Microcomputer Applications, 2023, 39(9): 82-86.
[2] Wang H, Shan H, Song Y, et al. Construction of 3D Foundation Design Scenes for Transmission and Transformation Engineering Based on GIM Technology [J]. Automation Technology and Applications, 2025, 44(1): 132-136.
[3] Kennedy J, Eberhart R. Particle swarm optimization[C]//Proceedings of IEEE International Conference on Neural Networks. Perth, Australia: IEEE, 1995: 1942-1948.
[4] Gomez J, Montesinos A, Lopez J. Improved particle swarm optimization for high-voltage transmission line routing[J]. IEEE Transactions on Power Systems, 2018, 33(2): 1987-1995.
[5] Zhang L, Chen S, Li J. Design and application of QR code-based 3D artificial targets for multi-source data registration[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 4689-4698.
[6] Peterson M, Gärtner K, Höfle B. LOD-based visualization of massive LiDAR point clouds for power line corridor monitoring[J]. Computers & Geosciences, 2020, 143: 104558.
[7] Yang S. Intelligent Quality Inspection Method for Transmission and Transformation Projects Based on 3D Technology [J]. Telecom World, 2023, 30(6): 94-96.
[8] Liu Q, Luo Y, Chen C, et al. Design of an Intelligent Auxiliary Control System for Substations Based on 3D Models [J]. Science and Engineering, 2023, 23(31): 13430-13437.
[9] Zhang X, Wang H, Meng Y, et al. 3D Digital Twin-based Transmission and Transformation Line Digital Simulation System [J]. Automation Technology and Applications, 2025, 44(2): 94-99.
[10] Sun M, Xia G. Cost Optimization of Transmission Line Projects Based on 3D Design [J]. Electrical Applications, 2025, 44(6): 80-85.
[11] Zhang Y, Ma W, Zhang C, et al. Integrated Analysis of Transmission and Transformation Towers Based on Image Recognition and CAE Simulation Technology [J]. Journal of Shandong University (Engineering Edition), 2023, 53(6): 122-130.
[12] Xiao H, Xu Z, Wu X, et al. Application of a 3D Digital Interoperability Handover System for Transmission and Transformation [J]. Power Information and Communications Technology, 2023, 21(9): 82-88.
[13] Wang C, Xia K, Chen T. Multi-dimensional Real-time Cloud Detection of Deep Foundation Pit Deformation in Power Transmission and Transformation Infrastructure Sites [J]. Computer Simulation, 2025, 42(9): 467-471.
[14] Xu Q, Hu H. Design and Implementation of a Digital Building Room Management System Based on Image Custom Tag Technology [J]. Broadcast and Television Technology, 2023, 50(11): 106-111.
[15] Ning H. Research and Design of a Digital Safety Management System for Energy Aluminum Sheet and Strip Equipment [J]. Electronic Technology and Software Engineering, 2022, (10): 187-190.
[16] Deng Y, Sun B, Li X, et al. Big Data-based Cost Trend Forecasting for Transmission and Transformation Projects [J]. Hunan Electric Power, 2023, 43(2): 108-111.
[17] Zhang H, Wu X, Shen X, et al. Cost Forecast Model for Transmission and Transformation Projects Based on BP Neural Network Optimization Algorithm [J]. Journal of Shenyang University of Technology, 2023, 45(4): 381-386.
[18] Wang S, Wen Q, Wang L, et al. Cost Management of Power Grid Transmission and Substation Project Based on BIM Technology [J]. Applied Mathematics and Nonlinear Sciences, 2023, 8(2): 1433-1446.
[19] He L, Huang B, Shen Y, et al. Key Data Processing Methods for All-in-Process Transmission and Transformation Projects Based on Hybrid Intelligent Optimization Algorithms [J]. Journal of Shenyang University of Technology, 2024, 46(3): 263-269.
[20] Cao J, Zhang S. Cost Prediction and Decision Analysis for Transmission and Transformation Cable Routes Based on Big Data [J]. Smart China, 2024, (8): 88-89.
[21] Li Z, Wang N, Liu A. Progress of Geodesy Related Ionosphere from Chinese Scientists in the Period of 2019-2023[J].Journal of Geodesy & Geoinformation Science.2023,(3).115-123.
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