| This thesis is inspired by the emerging technique of remote structural health monitoring (S.H.M). The primary focus of this thesis is to explore the signal process using wavelet transformation. Monitoring health of a structure wirelessly is a large task, which requires an integration of expertise from a variety of fields. This thesis is not meant to be exhaustive in this subject; however, it concentrates on the making of a finite element model of a specific bridge structure and a wavelets implementation. Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale.; In order to confidently propose this hypothesis and future implementations, a reliable computational reproduction of a structure is necessary. Structural System Identification (S.S.I.) is a procedure which allows engineers to verify and calibrate detailed computational models based on the physical attributes of an actual structure. The computational model is then subjected to artificial excitation. The goal is to obtain time history responses similar to a tangible testing. By using wavelet transformation as the primary analytical tool, one can closely inspect the subtle differences between the intact state and damaged state responses.; This technique will eventually allow the operator to monitor multiple structures and generate useful information by integrating feedbacks. In addition to the conclusive hypothesis of remote structural health monitoring, this thesis also proposes the idea of using such technique as an emergency management aid and its governmental and commercial implementation. |
