Foreword

Structural health monitoring aims to understand the condition of a structure based on sensor measurements, which are typically affected by noise and errors. Similarly, the relationship between observations and structural state is often nondeterministic. Key questions are how to provide a reliable and robust diagnosis, properly accounting for uncertainties, and how to bridge the gap between the data acquisition and decision making on such issues as structural maintenance, repair and replacement. The goal of this special issue is to gather together civil SHM cases where complex uncertainty problems have been successfully solved using probabilistic data interpretation methods. The six papers in this special issue do not require extraneous elucidation