Structural health monitoring (SHM) received in the last twenty years, a growing interest by both research- ers and professional, as pointed out by the number of monitoring systems installed today in various countries of the world. The main reasons for this development are on one side the limitations related to the use of traditional methods based on visual inspections an on the other side the great potential offered by automatic systems of damage detection allowing a preventive as- sessment of the seismic vulnerability and a sensible reduction of maintenance costs.
The aim of the Special Issue is to report recent advances in this field and successful applications. It includes eight papers from several research groups that have devoted considerable effort to the identification of techniques and tools for the application of SHM to structures in seismic areas.
For seismic-prone structures, health monitoring can sometimes take advantage of real responses recorded during strong earthquakes. These occurrences have a strategic importance both for the advancement of knowledge on the behavior of structures under strong seismic actions and for the calibration of realistic and reliable numerical models, able to reproduce the structural behavior and to formulate a diagnosis about possible sources of damage. Furthermore, the possibility to assess the seismic vulnerability based on data recorded on the monitored structure, opens new avenues in maintenance policies, shifting from a traditional ‘scheduled maintenance’, to a ‘condition-based maintenance’, carried out ‘on demand’, basing on the current structural condition.
The papers by Saisi et al. and Ranieri et al. tackle this subject for the specific case of historical masonry towers which are important landmarks in the Italian heritage, severely hit by the Emilia earthquake of 2012. The two papers present techniques for assessing the seismic vulnerability by means of preventive non destructive testing based on ambient vibrations taking into account environmental changes as well. The preventive assessment of the seismic vulnerability is also the subject of the paper by Ditommaso et al. focusing on irregular buildings, for which heavy structural damage is often due to torsional effects. In the paper is proposed a simplified experimental approach to identify the existence of torsional modes, based on a limited number of sensors thus limiting the cost of the monitoring system.
In recent years, thanks to the innovations in sensors and techniques for data transmission, a challenging goal for permanent seismic monitoring networks is developing: the possibility to quickly detect damage in a structure affected by a seismic event. This can be of crucial importance both for the management and coordination of immediate safety interventions or evacuation operation, and also for planning of the first operations of repair of damaged structures. In the aftermath of a strong seismic event this assessment is carried out using traditional methods based primarily on visual inspection that require quite a long time to cover the entire area affected by the earthquake, and also lead to estimations which are typically conservative, certainly on the safety side, but with a correspondent increase of the costs related to the downtime of the structure. Furthermore they may fail if damage is not visibly evident. Networks of sensors permanently installed on the structure supported by efficient damage identification algorithms constitute a promising alternative, able to provide real time information and a quick assessment of the damage state of the building after a seismic event. The application of algorithms for damage detection and localization to structures in seismic prone areas is the subject of the papers by Guéguen et al., Ponzo et al, Limongelli et al. and Benzoni et. al. that present numerical and experimental applications of different damage localization algorithms based on modal or non modal features. Sharing the same challenging goal the paper by Hernandez-Garcia et al. implements a robust data-driven methodology for detecting, locating and quantifying changes not only in linear structural parameters but also in nonlinear characteristics of chain-like systems.
The Guest Editor wishes to thank Dr. Gianmario Benzoni, Editor of the Journal, for his support, supervision and assistance in producing this special issue and also all the Authors and the Reviewers for their work and contribution.