摘要: |
Movable bridges have particular maintenance issues, which cost considerably more than those of fixed bridges, mostly because of the complex interaction of the mechanical, electrical and structural components. In order to track maintenance and operational performance, a comprehensive monitoring system was implemented on Sunrise Bridge (Ft. Lauderdale) to track the behavior and condition of several critical mechanical, electrical and structural components. In this project, a number of statistical analysis and machine learning-based methods were developed and employed to track the operation of the mechanical components. After the completion of the previous phases of the project, the bridge was scheduled for painting; however, the monitoring system was significantly damaged during the preparation, sandblasting and painting despite the considerable efforts of FDOT personnel to protect the system. The research team focused on repairing the monitoring system, which was affected by the painting operation, collecting and analyzing more data and preparing the system for FDOT. In this phase, the monitoring system was maintained. Details of the field work conducted to repair the damaged monitoring system are presented. Then, analysis of data that were collected after the monitoring system was repaired is presented for different mechanical components. The baseline response and the thresholds for acceptable behavior were established. |