Global vibration-based methods in the field of structural health monitoring are intended to capture structural stiffness changes of buildings or other civil engineering structures. Natural frequencies of buildings or bridges are commonly used parameters to monitor these stiffness changes. Therefore, it is essential to clarify the limit at which this method is no longer sensitive enough to be useful for structural health monitoring purposes. This paper numerically investigates the effect of structural damage and soil–structure interaction on cellular-type reinforced concrete buildings’ natural frequencies. These buildings are a common housing stock of Eastern Europe but are rarely investigated in this context. Comparisons with a reinforced concrete frame and infill structure building are made. Finite element models representing three structural system types of nine-story reinforced concrete buildings were used for the numerical simulations. Furthermore, a five-story finite element model was used for a damage sensitivity comparison. It is established that, for cellular-type structure buildings to detect damage comparable to that investigated in the paper, structural health (fixed base model frequency) should be monitored directly. Then, a statistical significance level for frequency changes of no more than 0.1% should be adopted. Conversely, the rocking frequency is a very sensitive parameter to monitor building base condition changes. These changes are often a cause of the cracking of building elements.

Structural health monitoring (SHM) provides an opportunity to assess and predict changes in the technical condition of structures during the operation of a building. Structural damage, as well as several operational and environmental conditions, causes changes in modal parameters. Temperature is the most popular environmental condition which is used for research. However, to the authors’ knowledge, this is the first investigation that highlights the effect of groundwater level change on the natural frequencies of the buildings and the impact of possible damage detection features. Groundwater level change can influence structural health monitoring measurements and cause faulty structural damage identification using vibration-based methods. This paper aims to analyse the impact of the groundwater level changes on the modal parameters of mid-rise reinforced concrete buildings. The modal parameters of mid-rise reinforced concrete buildings are determined using finite element (FE) models. Three different FE models of structural system types of nine-storey reinforced concrete (RC) buildings with shallow foundations are used to determine the impact of groundwater level fluctuation on the values of the buildings’ natural frequencies. Changes in the groundwater level have an impact on the natural frequencies of the mid-rise reinforced concrete buildings. This research proposes a new environmental condition that has to be considered to identify the structural damage using the vibration-based method. It is found that groundwater level rise causes a decrease in the natural frequency value. In this research, it is established that the influence of the groundwater level on the natural frequencies of the buildings can change abruptly, and there is a non-linear correlation between groundwater level change and natural frequencies of the buildings. The natural frequencies of the buildings can change under varying environmental conditions as well as in the case of structural damage. To identify structural damage in the long-term structural health monitoring measurements, it is recommended to select features which are sensitive to structural damage but are not affected by groundwater level change. Data normalisation and elimination using linear correlation methods can be used for short-term SHM under varying seasonal groundwater level change.

One of the limitations of using glued connections in practice is related to the need for connection quality control. Still, the need for the non-destructive quality control of finished products to determine the compliance of the developed structure with the designed one still exists. Considering the small amount of research on timber–concrete composites with glued connections, there is a lack of research on non-destructive methods for the quality control of rigid connections in timber–concrete composite structures. During the literature analysis, no information was found on the possibilities of testing the quality of the rigid timber-to-concrete connection. Therefore, two well-known methods—operational modal analysis and ultrasonic testing—were tested to verify the possibilities of applying these methods in determining defects in the rigid glued connection between the concrete and timber layers in the timber–concrete composite structures. A series of small-scale specimens produced by the stone chips method with and without artificially made defects in the timber-to-concrete adhesive connection was tested by both methods. Operational modal analysis shows significant changes in mode shape, frequency values, and spectral density diagrams. Despite the sufficiently large reflection of the ultrasonic signal on the timber and concrete boundary, the transmitted signal is sufficient to perform local ultrasonic tests for detecting defects in the adhesive connection. Thus, it is concluded that the principles of both methods can be applied in practice, and further research is needed to develop testing technology.

Strategically important objects, such as dams, tunnels, bridges, and others, require long-term structural health monitoring programs in order to preserve their structural integrity with minimal downtime, financial expenses, and increased safety for civilians. The current study focuses on developing a damage detection methodology that is applicable to the long-term monitoring of such structures. It is based on the identification of resonant frequencies from operational modal analysis, removing the effect of environmental factors on the resonant frequencies through support vector regression with optimized hyperparameters and, finally, classifying the global structural state as either healthy or damaged, utilizing the Mahalanobis distance. The novelty lies in two additional steps that supplement this procedure, namely, the nonlinear estimation of the relative effects of various environmental factors, such as temperature, humidity, and ambient loads on the resonant frequencies, and the selection of the most informative resonant frequency features using a non-parametric neighborhood component analysis algorithm. This methodology is validated on a wooden two-story truss structure with different artificial structural modifications that simulate damage in a non-destructive manner. It is found that, firstly, out of all environmental factors, temperature has a dominating decreasing effect on resonance frequencies, followed by humidity, wind speed, and precipitation. Secondly, the selection of only a handful of the most informative resonance frequency features not only reduces the feature space, but also increases the classification performance, albeit with a trade-off between false alarms and missed damage detection. The proposed approach effectively minimizes false alarms and ensures consistent damage detection under varying environmental conditions, offering tangible benefits for long-term SHM applications.