Simulation-Based Data-Driven Damage Detection for Highway Bridge Systems: SEMM Seminar with Dual Presentations

Seminar | November 27 | 12-1 p.m. | 502 Davis Hall

 Xiao Liang, Department of Civil & Environmental Engineering, UC Berkeley

 Civil and Environmental Engineering (CEE)

Highway bridges are one of the most critical components in transportation infrastructure systems. Accumulated Internal and concealed damages, due to aging or extreme events (e.g. earthquakes), make highway bridges vulnerable and pose a threat to the resiliency of local community. Therefore, these damages should be detected through structural health monitoring (SHM) algorithms at an early stage. Instead of treating SHM as an inverse problem, data-driven SHM utilizing the robust nonlinear time history analysis is explored. The first part of the presentation will focus on the development of a robust nonlinear solution algorithm for structural dynamics based on the Lyapunov stability theory. The main idea is to reformulate the equations of motion into a hypothetical dynamical system characterized by a set of ordinary differential equations. The second part will present several data-driven SHM approaches (e.g. feature selection, pattern recognition algorithms) and their application on damage detection of highway bridge systems. Very promising results (estimation accuracies) are observed on both binary (e.g. collapse vs. non-collapse) and multi-class (e.g. damage severity) classifications.