Research and Application of Intelligent Interaction Technology for Converter Station Equipment Operation and Maintenance Based on Spatial Computing

To address the challenges of low operational efficiency in HVDC converter station equipment maintenance and the inherent limitations of traditional manual inspection modes, this paper proposes an intelligent interaction platform for converter station operation and maintenance based on spatial computing technology. The platform establishes a collaborative architecture comprising four core modules—data acquisition, processing, recognition & localization, and intelligent interaction—by integrating binocular stereo vision, LiDAR point cloud scanning, and SLAM spatial positioning technologies. This architecture enables dynamic mapping between the physical environment and digital twin models. Specifically, the data acquisition module employs a multi-sensor fusion strategy, combining binocular vision triangulation with LiDAR point cloud coordinate transformation to reconstruct 3D equipment scenes. The recognition and localization module achieves precise device identification and real-time pose tracking through ORB feature extraction and SLAM algorithms. The intelligent interaction module incorporates augmented reality (AR) technology to provide on-site operational guidance and remote collaborative assistance, significantly enhancing maintenance efficiency and operational safety. Experimental results demonstrate that the platform effectively reduces routine inspection workload and enhances operational reliability.