Intelligent Platform for Model Updating in a Structural Health Monitoring System

The main aim of this study is to develop an automated smart software platform to improve the time-consuming and laborious process of model updating. We investigate the key techniques of model updating based on intelligent optimization algorithms, that is, accuracy judgment methods for basic finite element model, parameter choice theory based on sensitivity analysis, commonly used objective functions and their construction methods, particle swarm optimization, and other intelligent optimization algorithms. An intelligent model updating prototype software framework is developed using the commercial software systems ANSYS and MATLAB. A parameterized finite element modeling technique is proposed to suit different bridge types and different model updating requirements. An objective function library is built to fit different updating targets. Finally, two case studies are conducted to verify the feasibility of the techniques used by the proposed software platform.