China Achieves First-Ever AI-Assisted Railway Beam Replacement with Millimeter Precision

In the early hours of September 10 in Shaoxing, Zhejiang, China achieved a groundbreaking milestone in railway engineering. Backed by cutting-edge Artificial Intelligence (AI), a massive 4,000-ton steel box girder was positioned with millimeter-level precision—marking the first-ever use of AI in replacing an operational railway bridge beam. This pioneering success introduces a new benchmark for upgrading and modernizing China’s existing rail infrastructure.

The Shaoxing Intercity Railway, converted from the existing Xiaoshan–Ningbo Railway, is a key cross-city commuter link. Keqiao Station, the project’s newly built stop, holds the distinction of being China’s first elevated station added to an active railway line. With a total building area of around 3,600 square meters and a layout of two platforms and four tracks, it required a critical transformation: replacing the “throat section” concrete beams with steel box girders to accommodate the expanded track configuration.

This was no ordinary replacement task. Situated along the busy Xiaoshan–Ningbo Railway mainline, the project faced extreme technical complexity, high safety risks, and tight clearances—the new steel girder had to be pushed 21 meters into position with only a 10-centimeter gap at each end. Traditional methods simply couldn’t meet the precision and safety demands.

To overcome these challenges, China Railway 24th Bureau teamed up with leading universities to develop specialized synchronized pushing equipment, enhanced with an AI “brain.” Leveraging digital twin technology, they built a 3D model of the structure and deployed 40 high-precision sensors to capture real-time girder position data—ensuring stability, accuracy, and speed while minimizing disruptions to railway operations.

The AI system integrated three core modules—Perception, Simulation, and Control:

• Perception Module (the “Eyes”): Using advanced optical gratings, draw-wire sensors, strain gauges, and BeiDou satellite positioning to monitor movement in real time and prevent deviation.
• Simulation Module: Running a full digital rehearsal of the pushing process to detect and resolve potential issues before execution.
• Control Module: Coordinating 36 lifting jacks and 10 pushing jacks in perfect sync for a seamless beam swap.

AI also played a crucial role in the bridge design stage. Engineers from the Fourth Railway Institute created a finite element analysis model tailored to the complex stress distribution of railway turnout bridge zones. This allowed precise simulations of rail pressures, structural stress shifts, and displacement responses—meeting the demanding timeline and precision needed for immediate post-installation operation.

By dawn on September 10, the team had successfully removed a 4,086-ton old girder and installed a 4,389.6-ton new one, keeping vertical and horizontal deviations within just 2mm and 3mm respectively—an engineering triumph that signals a bold new era for AI-assisted railway construction in China.