Publications / 2011 Proceedings of the 28th ISARC, Seoul, Korea

Auto-Regressive Compensation Technique for a Reliable Non Invasive Structural Health Monitoring System

Berardo Naticchia, Massimo Vaccarini, Alessandro Carbonari, Pierpaolo Scorrano
Pages 826-831 (2011 Proceedings of the 28th ISARC, Seoul, Korea, ISBN 978-89-954572-4-5, ISSN 2413-5844)
Abstract:

Detecting the health status of buildings is critical to produce correct diagnoses that could prevent many pathologies, as well as driving maintenance interventions through timely and well targeted operations. The constant innovation in the development of low power wireless sensing devices provides an unparalleled chance to develop efficient monitoring system prototypes, conceived to be very low intrusive and operating in real-time, that can be applied also on existing buildings, without any need to predispose chases for power conveyance or communication cables. Its adoption is expected to be useful not only for standard health status monitoring of buildings during their lifecycle, but also for automated monitoring of old buildings during the execution of renovation works. The latter being referred to the possibility that unexpected collapses may endanger the conditions of workers engaged on the construction-site, where alerting in advance would prevent many deaths on the job. In this paper a low-power, wireless, easily installable structural monitoring system based on tilt sensors is developed, on which several integrated logics for automated control of building’s health conditions are implemented. As its preliminary evaluation on a real building demonstrated that external temperature variations cause inaccurate measurements, an experimental setup capable of reproducing dynamic conditions due to environmental actions on the system has been developed. It was used both for developing an autoregressive model to be implemented for temperature compensation, and to perform its validation. The technologies and logics for remote automated monitoring are presented.

Keywords: Structural health monitoring, real-time control, dynamic temperature compensation, autoregressive models