Signal Processing Methodology of Response Data from a Historical Arch Bridge toward Reliable Modal Identification

Abstract

The paper is part of a case study concerning the structural assessment of a historical infrastructure in the local territory, a road three-span reinforced concrete arch bridge over a river, built by the end of World War I (1917). The purpose of the paper is twofold: first, in-situ acquired response data are systematically analysed by specific signal processing techniques, to form a devoted methodological procedure and to extract useful information toward possible interpretation of the current structural conditions; second, the deciphered information is elaborated, in view of obtaining peculiar conceptualisations of detailed features of the structural response, as meant to achieve quantitative descriptions and modelling, for final Structural Health Monitoring (SHM) and intervention purposes. The proposed methodology, integrating self-implemented and adapted classical signal processing methods, and refined techniques, such as Wavelet analysis and ARMA models, assembles a rather general, systematic methodological approach to signal processing, highlighting the capability to extract useful and fundamental information from acquired response data, also endowed of a non-stationary character, toward final structural interpretation, identification and modelling, thus enabling for developing a reliable and effective SHM platform, on strategic ageing infrastructures. For the present case study, non-stationary characteristics of the response signals are revealed and flattened out, to identify the underlying fundamental frequencies of the infrastructure and to advance particular interpretations of its current structural behaviour, informing an enlarging structural consciousness of the bridge at hand.

Optimised Structural Modelling for Inverse Analysis Parameter Identification Relying on Dynamic Measurements

“…Pursuing the goals of this research branch, the present paper sets an Inverse Analysis problem based on modal properties, first on a simple archetypal structure and, then, on a specific case study, namely a historical reinforced concrete arched bridge, that is Brivio bridge (1917) [32], located in Northern Italy. The bridge, given its still crucial infrastructural role and historical value, has been subjected, in recent years, to monitoring experimental campaigns and to subsequent response signal processing (see, e.g., [33,34,35,36]) and structural modelling and identification (see, e.g., [37,38]), as also enquired in the present contribution and in companion work [39].…”

Inverse Analysis Investigation by Gaussian Processes Optimisation of a Historical Concrete Bridge Relying on Dynamic Modal Measurements

“…Several instrumentation systems were adopted during the test phases, in particular: ten uniaxial wired piezoelectric accelerometers, seven wireless sensors, four QDaedalus system total stations and a laser scanner; simultaneous dynamic testing and measurement of the structure, under regular operational traffic loading conditions, were defined also according to diverse setups. In the present work, experimentally identified quantities are acquired from previously processed data, while details on experimental identification and response signal processing may be found, respectively, in [29] and [28], with reference both to single span and whole bridge analysis.…”

“…Specifically, the considered case study focuses on a historical reinforced concrete arched bridge, Brivio bridge, located in Northern Italy [24]. The bridge, both for hits historical value and its crucial, currently active, infrastructural role, has recently been the subject of a thorough study supported by experimental campaigns, followed by response signal processing and deciphering (see, e.g., [25,26,27,28]) and by property identification, model calibration and structural diagnosis (see, e.g., [29,30,31,32]).…”

Computer-Aided Structural Diagnosis of Bridges Using Combinations of Static and Dynamic Tests: A Preliminary Investigation

“…In current Structural Engineering, growing research and application trends point toward the diagnostic identification and assessment of structures and infrastructures, for characterization and monitoring aims [1,2]. Within such a broad field, particular interest is devoted to bridge structures, for their key infrastructural role and, frequently, historical value [3][4][5]. Recent applications can be found in the literature based on various methodologies and goals, such as employment of Artificial Intelligence [6,7], selection of measurement systems and sensors [8][9][10], damage detection [11][12][13], and, specifically, for reinforced concrete bridges [14][15][16][17].…”