This monograph assesses in depth the application of recursive Bayesian filters in structural
health monitoring. Although the methods and algorithms used here are well established in the
field of automatic control their application in the realm of civil engineering has to date
been limited. The monograph is therefore intended as a reference for structural and civil
engineers who wish to conduct research in this field. To this end the main notions underlying
the families of Kalman and particle filters are scrutinized through explanations within the
text and numerous numerical examples. The main limitations to their application in monitoring
of high-rise buildings are discussed and a remedy based on a synergy of reduced order modeling
(based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance
and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental
evaluations.
