Charles R. Farrar

TL;DR: In this article, a novelty detection technique is developed explicitly taking into account these natural variations of the system in order to minimize false positive indications of true system changes, such as structural deterioration and damage.

TL;DR: In this article, a comparison of the statistics on the measured model parameters of a bridge structure to the expected changes in those parameters caused by damage is presented, and it is then determined if the changes resulting from damage are statistically significant.

TL;DR: In this paper, a new wireless sensing network paradigm is presented for structural monitoring applications, where both power and data interrogation commands are conveyed via a mobile agent that is sent to sensor nodes to perform intended interrogations, which can alleviate several limitations of the traditional sensing networks.

TL;DR: In this article, a sensor self-diagnostic procedure that performs in situ monitoring of the operational status of piezoelectric active sensors and actuators in structural health monitoring (SHM) applications has been proposed.

TL;DR: An algorithm with a Bayesian approach based on a Markov-chain Monte Carlo method to cluster structural responses of the bridges into a reduced number of global state conditions, by taking into account eventual multimodality and heterogeneity of the data distribution is proposed.