This paper targets the frequency domain identification of current structural modal properties under earthquake excitation. A new refined Frequency Domain Decomposition (rFDD) algorithm is implemented towards the output-only modal dynamic identification of heavy-damped frame structures, which are subjected to a wide set of strong ground motions. In fact, both seismic excitation and/or high damping values shall not fulfil traditional FDD assumptions. Despite that, with the present rFDD implementation quite limited errors in the modal parameter estimates have been achieved, including for the modal damping ratios (ranging from 1% to 10%). At first, the identification technique is formulated and explored analytically, by proving its potential effectiveness with seismic response input. Then, all strong motion modal parameters are consistently identified. As a fundamental necessary condition, synthetic response signals are adopted. These have been generated prior to dynamic identification from computed numerical seismic responses of a set of shear-type frames. The efficiency of the present original implementation is highlighted, by proving that consistent rFDD modal dynamic identification of structures at seismic input and simultaneous heavy damping looks feasible. Thus, the paper delivers a robust method for inspecting current structural modal properties of frame buildings under earthquake excitation and for observing their possible variation along experienced seismic histories.

Due to the increasing quest of adopting low-cost sensors in structural health monitoring (SHM) processes, which may lead to detecting signals contaminated by significant levels of noise, the need to devise appropriate and effective denoising strategies, at the post-processing stage, is becoming more and more essential. Among several approaches proposed in the literature, it has been demonstrated that the employment of discrete wavelet transform (DWT) as a multi-rate filter bank, as well as the use of singular value decomposition (SVD), may result to be quite effective in signal denoising within various research fields, as biological, acoustic and mechanical. Here, DWT- and SVD-based denoising techniques are first independently reconsidered and reimplemented, aiming at exploring their optimal calibration in purifying noise-corrupted vibration response signals encountered in civil engineering applications. Then, a systematic performance evaluation is provided within a comparative framework, developed at an increasing level of noise affecting the measurements, in terms of noise-to-signal (N/S) ratio. In the study, two specific classes of synthetic response signals are first considered, namely earthquake and ambient vibration signals, since they may be assumed as representative of more general non-stationary and stationary signal typologies, respectively. To achieve a complete description of the clarified signal, strengths and weaknesses of the two denoising approaches are explored, in both time and frequency domains. The results prove the effectiveness of the analyzed implementations, especially in purifying seismic response signals, while some limitations may arise concerning the treatment of ambient vibration signals, in particular for the DWT-based denoising technique. Finally, a real case study is analyzed, where both denoising approaches are adapted and employed for clarifying acceleration signals detected on a modern short-span railway bridge, with rather satisfactory results, for both techniques.

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.

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, in forming an enlarging structural consciousness of the bridge at hand.