Development of Cable Tunnel Monitoring System Based on ACO Optimization Neural Network in Smart Grid

With the accelerated urbanization process and escalating demand for electrical energy, the operational safety and stability of cable tunnels have emerged as critical components in modern power infrastructure systems. This study presents an innovative multi-modal monitoring system featuring a hierarc...

Full description

Saved in:
Bibliographic Details
Published inInternational Symposium on Autonomous Systems (Online) pp. 1 - 6
Main Authors Wang, Shuo, Dong, Liwen, Lang, Yaoming, Zhang, Mingde, Li, Zhihua, Guo, Fanghong
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.05.2025
Subjects
Ant Colony Optimization
cable tunnel
comprehensive environmental monitoring
Computational modeling
Data acquisition
Environmental monitoring
Geographic information systems
Neural networks
Power system stability
Safety
Smart grids
Stability analysis
Thermal stability
Online AccessGet full text
ISSN2996-3850
DOI10.1109/ICAISISAS64483.2025.11052186

Cover

More Information
Summary:With the accelerated urbanization process and escalating demand for electrical energy, the operational safety and stability of cable tunnels have emerged as critical components in modern power infrastructure systems. This study presents an innovative multi-modal monitoring system featuring a hierarchical distributed architecture that establishes a closed-loop framework integrating real-time data acquisition with intelligent analytical applications. The proposed system employs an array of advanced detection technologies, including high-precision sensor networks, distributed fiber-optic temperature sensing (DTS), and adaptive wireless transmission protocols, to achieve comprehensive environmental monitoring of tunnel structures. A novel hybrid algorithm combining Back Propagation (BP) neural networks with Ant Colony Optimization (ACO) metaheuristics has been developed to synergistically enhance fault prediction accuracy while optimizing computational efficiency. The integration of 3D/Building Information Modeling (BIM) visualization techniques with Geographic Information Systems (GIS) spatial analysis enables dynamic condition mapping and data-driven decision support through spatiotemporal modeling of tunnel parameters. This research advances intelligent monitoring methodologies for underground utilities and offers practical insights for next-generation smart grid development.
ISSN:2996-3850
DOI:10.1109/ICAISISAS64483.2025.11052186