An innovative framework for structural health monitoring of long-span bridges

Abstract

Structural Health Monitoring (SHM) of structures has received a wide diffusion and development in the last decade as, for instance, in the fields of sensing technologies, data migration facilities and data pre/post processing algorithms. Many of these leaps have found their first application on monitoring of bridges which are among the most crucial structures because of both their importance in the economic activities of a country and the relevance of the economic effort necessary for their construction and maintenance. Within this context the SHM aimed at the continuous condition assessment of bridges not only seems to be very promising for increasing the cost-effectiveness of the maintenance procedures but can be still considered a challenge. To this purpose tools based on multivariate statistical analysis are becoming very popular for automatically revealing the existence of damage in structures using vibration data under changing environmental and operational conditions. In the present PhD Thesis, considering natural frequencies as damage-sensitive features, multivariate statistical analysis are newly applied for monitoring the structural health state of bridges, accounting for the linear and nonlinear correlations between such dynamic features and the environmental and operational conditions. A procedure based on the continuous modal frequencies tracking, Principal Component Analysis and Novelty Detection is proposed. Its effectiveness and capability in damage detection are previously tested on the pseudo-experimental response data of an analytical parametric model of suspension bridge with damage in one main cable and subjected to wind loading and changing temperature. Then, for an absolutely realistic representation of the operational and environmental conditions, the same technique is tested on long-term real bridge data. The results demonstrate the feasibility of permanent monitoring systems (PMS) for the real-time condition assessment of bridges and the robustness of the proposed procedure in revealing the existence of damage. Despite the effects induced on frequencies by damage are of the order of few per mil, in any case smaller than those induced by environmental and operational conditions, the adopted statistical technique allows to reveal its occurrence in a reliable and prompt manner. Moreover, the absolute general nature of the proposed approach may reveal in perspective, its extension to any other structure equipped with a PMS.