In this paper, a dynamic testing and corresponding signal processing methodology is presented for condition assessment of bridge structures, via use of a diverse and potentially dense grid of low-cost and easily deployable monitoring technologies. In particular, wireless and non-contact sensors are simultaneously deployed on a historic reinforced concrete bridge in order to record acceleration and dynamic displacement response, under operational loading conditions. An innovative monitoring approach is proposed on both the hardware (sensors) and software (algorithmic) front, in which an effective data fusion procedure is adopted for fusing these alternative technologies for vibration-based monitoring in terms of both acceleration and displacement information. The demonstrated efficacy of the fusion procedure on the case-study of an actual operating system, the historic Brivio bridge, reveals the potential of this approach within the context of structural monitoring, where acquisition of heterogeneous information certainly proves advantageous.

Abstract. This work attempts a comprehensive processing of response signals acquired from an experimental campaign on a local historical bridge using four different types of sensory systems. A general analysis setup is developed, allowing for consistent modal dynamic identification via individual signal processing as well as via data fusion through dedicated MultiRate Kalman filtering approach. The investigation reveals the potential and limitations in terms of utilization of novel instrumentation systems to be adopted for Structural Health Monitoring (SHM) purposes.

This paper compares three different methods capable of estimating the deflection of the vertical (DoV): one is based on the joint use of high precision spirit leveling and Global Navigation Satellite Systems (GNSS), a second uses astro-geodetic measurements and the third gravimetric geoid models. The working data sets refer to the geodetic International Terrestrial Reference Frame (ITRF) co-location sites of Medicina (Northern, Italy) and Noto (Sicily), these latter being excellent test beds for our investigations. The measurements were planned and realized to estimate the DoV with a level of precision comparable to the angular accuracy achievable in high precision network measured by modern high-end total stations. The three methods are in excellent agreement, with an operational supremacy of the astro-geodetic method, being faster and more precise than the others. The method that combines leveling and GNSS has slightly larger standard deviations; although well within the 1 arcsec level, which was assumed as threshold. Finally, the geoid model based method, whose 2.5 arcsec standard deviations exceed this threshold, is also statistically consistent with the others and should be used to determine the DoV components where local ad hoc measurements are lacking.

No abstract

No abstract