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This paper introduces a framework to perform operational modal analysis (OMA) for structural health monitoring (SHM) by presenting the development and validation of a low-power, solar-powered wireless sensor network (WSN) tailored for bridge structures. The system integrates accelerometers and temperature sensors for dynamic structural assessment, all interconnected through the energy-efficient message queuing telemetry transport (MQTT) messaging protocol. Moreover, it delves into the details of sensor selection, calibration, and the design considerations necessary to address the unique challenges associated with bridge structures. Special attention is given to the solar-powered aspect, allowing for extended deployment periods without the need for frequent maintenance or battery replacements. To validate the proposed system, a comprehensive field deployment was conducted on an actual bridge structure. The collected data were transmitted through MQTT messages and analyzed by means of OMA. Comparative studies with traditional wired systems underscore the advantages of the solar-powered wireless solution in terms of sustainability, scalability, and ease of deployment. Results from the validation phase demonstrate the system's capability to provide accurate and real-time data needed to assess the health state of the monitored asset. This paper concludes with insights into the practical implications of adopting such a solar-powered WSN, emphasizing its potential to revolutionize bridge health monitoring by offering a cost-effective and energy-efficient solution for long-term infrastructure resilience. [ABSTRACT FROM AUTHOR]

In 2018 a collaborative project between Politecnico di Milano (PoliMI) and Regione Lombardia (RL) was launched to join forces and expertise toward the improvement of the regional transport infrastructures maintenance management. One of the project goals was the development of regional guidelines aimed to support the design and implementation of monitoring systems for bridges. The focus of this paper is on the illustration of the Monitoring Regional (MoRe) guidelines and of their implementation on nine pilot monitoring systems designed and deployed within the project. The (MoRe) guidelines tackle the entire monitoring process from the analyses of the monitoring goals and the preliminary investigations needed to the identification of the phenomena and relevant indicators to monitor, up to the selection of monitoring devices and the presentation of results. A short illustration of the permanent monitoring systems installed on nine exemplary bridges in the Lombardia region concludes the paper. [ABSTRACT FROM AUTHOR]

Bridges and viaducts are facing growing traffic, increasing loads as well as ageing and deterioration. Nowadays, vibration‐based Structural Health Monitoring (SHM) represents an effective solution to extract quantitative information regarding bridge structural condition. Bridge frequencies are fundamental parameters capable to reflect and summarize bridge dynamics and health condition. Typically, their identification is performed by direct approaches, which rely on the use of sensors installed on the structure under analysis. A cost‐efficient, movable, and flexible alternative is offered by drive‐by methods, consisting in the use of instrumented vehicles to extract bridge frequencies. This paper presents an experimental campaign carried out on a multiple‐span mixed railroad bridge, with the aim to identify its frequencies through onboard measurements. A set of MEMS wireless accelerometers is deployed on the vehicle, firstly allowing for vehicle pitch component mitigation. Vehicle accelerations were then used to extract bridge frequencies, by means of a Most Probable Modal Frequencies approach, relying on synchrosqueezed wavelet transform. At a cruise speed of 30 km/h promising results in terms of indirect frequency estimation were found, with no traffic disruption. [ABSTRACT FROM AUTHOR]

Structural health monitoring of civil infrastructure, such as bridges and buildings, has become a trending topic in the last few years. The key factor is the technological push given by new technologies that permit the acquisition, storage, processing and visualisation of data in real time, thus assessing a structure's health condition. However, data related to anomaly conditions are difficult to retrieve, and, by the time those conditions are met, in general, it is too late. For this reason, the problem becomes unsupervised, since no labelled data are available, and anomaly detection algorithms are usually adopted in this context. This research proposes a novel algorithm that transforms the intrinsically unsupervised problem into a supervised one for condition monitoring purposes. Considering a bridge equipped with N sensors, which measure static structural quantities (rotations of the piers) and environmental parameters, exploiting the relationships between different physical variables and determining how these relationships change over time can indicate the bridge's health status. In particular, this algorithm involves the training of N models, each of them able to estimate the quantity measured via a sensor by using the others' N − 1 measurements. Hence, the system can be represented by the ensemble of the N models. In this way, for each sensor, it is possible to compare the real measurement with the predicted one and evaluate the residual between the two; this difference can be addressed as a symptom of changes in the structure with respect to the condition regarded as nominal. This approach is applied to a real test case, i.e., Candia Bridge in Italy, and it is compared with a state-of-the-art anomaly detector (namely an autoencoder) in order to validate its robustness. [ABSTRACT FROM AUTHOR]

The present study deals with the structural safety evaluation of a 50-year-old river bridge, called Baghetto Bridge, located in north Italy on the Adda River. Generally speaking, hydraulic processes are the main cause of bridge failure. Scour and hydrodynamic loads have been largely studied by the hydraulic engineering community; however, in practice, integration with structural analysis is often missing. The aim of this research is to provide a multidisciplinary procedure based on hydraulic and dynamic investigations devoted to the structural verification and monitoring of river bridges with traditional mechanical bearings. The deck–river interaction is addressed, studying the influence of debris accumulation on the bridge and performing structural verification of the bearing supports. The actions exerted on the bridge deck by the river current were estimated following the recommendations of the Italian code and making some further assumptions. In addition, dynamic investigations and FE modelling were performed. The results show (1) a relatively fast procedure that can be applied by practitioners to perform structural verification of river bridges with traditional mechanical bearings, and (2) an investigation method to evaluate temperature–frequency correlation as a reference for future inspections. [ABSTRACT FROM AUTHOR]