Sensing and information extraction towards a population based structural health monitoring (PBSHM) framework for bridges

PBSHM has been demonstrated on simple structures with few elements to date. Heterogeneous populations of structures (e.g. bridges) have not been explored yet. Therefore, the work in this thesis investigates the potential for implementing a PBSHM framework to bridges .

The work first checks that Irreducible Element Models can be used to describe bridges, and Attributed Graphs can be generated and compared for similarity. For a pool of six bridges, each described with IE models and compared as AG's, mode tests are carried out to check that similarity metrics between pairs of bridges are reflective of the similarity between their dynamic responses. A novel approach to calculating bridge displacement is then proposed that is robust across bridge and load types.

The approach is implemented to a set of similar beam and slab bridges, where it is observed that the bridges with high similarity metrics exhibit similar displacement responses from similar loading. Largely, the work of this thesis shows that a PBSHM approach to bridge SHM could potentially be implemented to facilitate knowledge transfer between bridges.