Development of integrated semi-active adaptive vibration control system for bridges subjected to traffic loads

Abstract

Nowadays, the fluid viscous damper is the most conventional energy dissipation system implemented in bridge structures to control the vibrations due to traffic loads. However, to effectively protect the bridge against frequent and severer vibrations, it is required to adapt the function of the damper according to the variable traffic loads. In this research, an Integrated Semi-Active Adaptive Vibration Control System is developed for the bridge structures. This control system consists of a Semi-Active Bypass Fluid Damper (SABFD), a programmable logic controller (PLC), pressure transducers, and displacement sensors. Semi-Active Bypass Fluid Damper is a hydraulic cylinder with a pair of external bypass pipes with motorized electric flow control valves which are installed in the middle of pipes to control the flow rate of the fluid. A programmable logic controller (PLC) is implemented to manage the operation of motorized valves according to the movement of the bridge.Therefore, the integrated control system is able to function as a real-time controller during its operation. To develop the control system, the performance of the SABFD device has been assessed through analytical model of the various control valve positions. Then, according to the structure response, a fuzzy control algorithm has been adapted in the PLC controller.Afterward, the prototypes of the SABFD and the PLC controller have been fabricated and a series of cyclic load tests have been conducted by using a dynamic actuator. The outcomes of the numerical analysis and results of the experimental tests revealed that the developed device is capable of generating a wide range of forces during device operation. The developed fuzzy control algorithm is then implemented to the finite element model of the bridge equipped with SABFD, and the results proved that the real-time control system effectively limits the bridge displacements according to the pre-defined fuzzy control rules.