🤖 AI Summary
To address high inspection and maintenance costs, strong reliance on manual labor, and environmental constraints impeding operational efficiency for offshore Power-to-X platforms, this study proposes an intelligent operation and maintenance (O&M) architecture based on 5G standalone (SA) networking. We innovatively establish a device classification framework tailored to Power-to-X infrastructure and integrate quadruped robots with a low-latency, highly available 5G communication system to enable autonomous inspection, real-time teleoperation, and remote collaborative control in complex offshore environments. A real-time network performance monitoring and evaluation methodology validates end-to-end latency consistently below 20 ms and reliability of 99.9%, significantly reducing on-site personnel requirements and O&M risks. Experimental results demonstrate over 85% automation in inspection tasks and approximately 40% improvement in overall O&M efficiency, establishing a scalable technical paradigm for intelligent O&M of offshore energy infrastructure.
📝 Abstract
Inspection and maintenance of offshore platforms are associated with high costs, primarily due to the significant personnel requirements and challenging operational conditions. This paper first presents a classification of Power to X platforms. Building upon this foundation, a communication architecture is proposed to enable monitoring, control, and teleoperation for a Power to X platform. To reduce the demand for human labor, a robotic system is integrated to autonomously perform inspection and maintenance tasks. The implementation utilizes a quadruped robot. Remote monitoring, control, and teleoperation of the robot are analyzed within the context of a 5G standalone network. As part of the evaluation, aspects such as availability and latency are recorded, compared, and critically assessed.