Study on the Evaluation Method of Truss Mechanical Performance in Old Factories Based on Bayesian Updating

This study focuses on the evaluation of the mechanical performance of trusses in old factory buildings. It innovatively applies the Bayesian updating theory to construct an evaluation system. Considering the uncertainties such as material aging and complex load histories existing in the trusses of old factory buildings, traditional evaluation methods are difficult to accurately describe the fluctuations in their structural performance. This method transforms these uncertainties into probabilistic expressions. By integrating historical inspection data, on - site monitoring data, and mechanical simulation data, and using rejection sampling to screen valid samples, a comprehensive and scientific structural performance evaluation framework based on probabilistic analysis is formed. Verified by practical cases, this framework can provide accurate parameter basis for truss reinforcement, effectively balancing safety and economy. In addition, this method has good universality and can be extended to the fields of safety assessment, protection, and utilization of historical buildings and other old industrial facilities, opening up a new path for the performance evaluation of related structures.