Research on Tower Construction Safety Monitoring System Based on Digital and Artificial Intelligence

Driven by the dual carbon strategy, intelligent operation and maintenance technology has become a key breakthrough in the digital transformation of the wind power industry. This study proposes an innovative solution for tower hoisting safety monitoring system based on the integration of digital twins and artificial intelligence. By constructing a three-dimensional visualized digital twin, it achieves deep interaction between physical entities and virtual models. The system integrates multi-source sensor networks to collect key indicators such as vibration spectra, stress distribution, and environmental parameters in real time. Combined with the improved YOLO algorithm, it realizes structural deformation detection during the lifting process, and uses LSTM time series prediction model to construct a tower dynamic stability evaluation system. Experimental data shows that the intelligent monitoring system improves inspection efficiency compared to traditional methods, achieves an accuracy rate of 97.3% in anomaly recognition, and controls response latency within 200ms through cloud based collaborative computing architecture.