Objective To achieve intelligent, high-precision and three-dimensional visualization of pipeline leakage detection in gas ground stations, a digital twin system for pipeline leakage detection in gas ground stations was designed and implemented by integrating digital twin and deep learning technologies.

Method The architecture of the digital twin system for gas ground stations was designed, and the digital twin of the gas ground station was constructed. The framework for pipeline leakage detection in gas ground stations was established by integrating digital twin and deep learning. The three-dimensional model of the gas ground station pipeline was built using 3D Max and imported into Unity3D for the construction of a three-dimensional visualization scene.

Result Combined with the pipeline leakage detection model of the gas ground station, the main functions such as three-dimensional visualization of the gas ground station model, intelligent detection of pipeline leakage in the gas ground station, and monitoring of equipment operation status were realized. The system can accurately identify pipeline leakage, optimize operation and maintenance decision-making, and present the overall appearance and pipeline health status of the gas ground station through a three-dimensional visualization interface, significantly improving management efficiency and fault response capability.

Conclusion It provides intuitive and efficient digital support for the operation and maintenance management of natural gas ground stations, realizes intelligent monitoring and management of gas ground station pipelines, and significantly improves the intelligent operation and maintenance level of the gas ground station pipeline system.