Abstract

To address the issues of vibration blind spots and the “black box” of quality control in the vibration process of precast beams caused by dense reinforcement zones and the arbitrariness of manual operation, this paper proposes the development of a closed-loop intelligent vibration system. This system integrates intelligent equipment, evaluation models, adaptive algorithms, and digital twin feedback control. By combining drum-type vibration robots for large-scale operations with wearable sensing devices for complex dead corners, full coverage of the operation area is achieved. Second, based on the coupling mechanism of mechanical-electrical-hydraulic multi-physics fields, a quantitative evaluation model for vibration compactness is established. Furthermore, a hierarchical adaptive control strategy based on feedback of the rheological state is designed. By fusing real-time positioning data with vibration energy indices, process parameters such as vibration frequency and duration are dynamically optimized. Finally, through the developed digital twin feedback control platform, a vibration energy cloud map reflecting the internal quality can be generated in real time, thereby achieving process visualization and early warning of defects. Results show that the system can accurately detect and resolve missed and insufficient vibration issues. Construction activities are thus managed via data rather than subjective empirical judgment.

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