Structural health monitoring (SHM) has been increasingly exploited in recent years as a valuable tool for assessing performance throughout the life cycle of structural systems, as well as for supporting decision‐making and maintenance planning. Although a great assortment of SHM methods has been developed, only a limited number of studies exist serving as reference basis for the comparison of different techniques. In this paper, the vibration‐based assessment of a small‐scale wind turbine (WT) blade is experimentally investigated, with the aim of establishing a benchmark case study for the SHM community. The structure under consideration, provided by Sonkyo Energy as part of the Windspot 3.5 kW WT model, is tested in both healthy and damaged states under varying environmental, that is, temperature, conditions as imposed by means of a climatic chamber. This study offers a thorough documentation of the configuration of this experimental benchmark, including the types of deployed sensors, the nature of excitation and available measurements, and the investigated damage scenarios and environmental variations enforced. Lastly, an overview of the raw and processed measurement data, made available to researchers via an open access Zenodo repository, is herein provided.

This paper constitutes the numerical companion of the experimental work on vibration‐based monitoring of a small‐scale wind turbine (WT) blade. In this second part, a numerical benchmark is established for condition assessment of a Windspot 3.5‐kW WT blade. The aim is to supplement the companion experimental work with a physical model exposed to diverse operational conditions, loading scenarios, and damage patterns that are not easily explorable and controllable in the laboratory. To this end, a finite element (FE) model of the considered blade is developed and subjected to a number of artificial damage scenarios, which are dynamically tested under both environmental and operational variability. The paper offers a detailed description of the numerical benchmark and the underlying assumptions, as well as the spectrum of operational conditions, the measured quantities, and the wind load model. Finally, we provide an overview and demonstration of the stand‐alone application for time history analysis and generation of synthetic vibration data, which is made available via an open‐access code in Sonkyo‐Benchmark repository.

Constructed in 1969, the Chillon viaducts constitute a vital component of the Swiss roadway network. The bridge deck was strengthened in 2015 by means of an Ultra High Performance Fiber Reinforced Cement-based Composite for alleviating the effects of deterioration that has been induced by Alkali-Silica Reaction. In order to assess the efficacy of this rehabilitation solution, and to further evaluate its long-term performance, a Structural Health Monitoring (SHM) campaign was implemented, relying on low-cost, yet easily deployable, sensors. The deployed monitoring solution includes a suite of accelerometers, strain gauges, temperature and humidity sensors. This work studies and reports on the influence of operational (traffic) and environmental (temperature and humidity) conditions onto structural performance, on the basis of monitoring data extracted form the first moths of the monitoring campaign. To this end, the monitoring data are initially processed by means of standard modal analysis methods, as well as non-stationary time-series analysis tools. In a second step, a finite element model of the system is built and updated, and subsequently exploited to deliver a comparison between the original and rehabilitated structure. Finally, by exploiting the updated system model, a reliability analysis is carried out, which confirms the efficiency of the strengthening solution.

The ground motion of an earthquake or the ambient motion of a large engineered structure not only has translational motion, but it also includes rotation around all three axes. No current sensor can record all six components, while the fusion of individual instruments that could provide such recordings, such as accelerometers or Global Navigation Satellite System (GNSS) receivers, and rotational sensors, is non-trivial. We propose achieving such a fusion via a six-component (6C) Kalman filter (KF) that is suitable for structural monitoring applications, as well as earthquake monitoring. In order to develop and validate this methodology, we have set up an experimental case study, relying on the use of an industrial six-axis robot arm, on which the instruments are mounted. The robot simulates the structural motion resulting atop a wind-excited wind turbine tower. The quality of the 6C KF reconstruction is assessed by comparing the estimated response to the feedback system of the robot, which performed the experiments. The fusion of rotational information yields significant improvement for both the acceleration recordings but also the GNSS positions, as evidenced via the substantial reduction of the RMSE, expressed as the difference between the KF predictions and robot feedback. This work puts forth, for the first time, a KF-based fusion for all six motion components, validated against a high-precision ground truth measurement. The proposed filter formulation is able to exploit the strengths of each instrument and recover more precise motion estimates that can be exploited for multiple purposes.

Ultra-high-performance fiber-reinforced cement-based composite (UHPFRC) has been increasingly adopted for rehabilitation projects over the past two decades, proving itself as a reliable, cost-efficient and sustainable alternative against conventional methods. High compressive strength, low permeability and high ductility are some of the characteristics that render UHPFRC an excellent material for repairing existing aged infrastructure. UHPFRC is most commonly applied as a surface layer for strengthening and rehabilitating concrete structures such as bridge decks or building slabs. However, its implementation with steel structures has so far been limited. In this work, the UHPFRC strengthening of a steel bridge is investigated both in simulation as well as in the laboratory, by exploiting a real-world case study: the Buna Bridge. This Croatian riveted steel bridge, constructed in 1893, repaired in 1953, and decommissioned since 2010, was removed from its original location and transported to laboratory facilities for testing prior to and after rehabilitation via addition of UHPFRC slab. The testing campaign includes static and dynamic experiments featuring state-of-the-art monitoring systems such as embedded fiber optics, acoustic emission sensors and digital image correlation. The information obtained prior to rehabilitation serves for characterization of the actual condition of the structure and allows the design of the rehabilitation solution. The UHPFRC slab thickness was optimized to deliver optimal fatigue and ultimate capacity improvement at reasonable cost. Once the design was implemented, a second round of experiments was conducted in order to confirm the validity of the solution, with particular attention allocated to the interface between the steel substrate and the UHPFRC overlay, as the connection between both materials may result in a weak contact point. A detailed fatigue analysis, based on updated FEM models prior to and after strengthening, combined with the results of a reliability analysis prove the benefits of adoption of such a solution via the significant extension of the structural lifespan.