University of Naples “Federico II” – School of Engineering

This interesting application describes  the modal-based SHM system recently installed at the School of Engineering Main Building of the University of Naples “Federico II”. This building has been for years the core of experimental research in the field of structural monitoring aimed at the seismic risk mitigation and management. The building is indeed characterized by a relevant architectural value, and it is located nearby the Campi Flegrei, a large and active volcanic area generating frequent seismic sequences. After some renovation works carried out in the building in recent years, the old monitoring system installed in 2006 was decommissioned. However, the recent occurrence of several earthquakes in the area associated with bradyseism motivated the design and installation of a new monitoring system in 2024.

Degradation phenomena, such as those due to aging, severe environment or fatigue, and damage induced by hazardous events, such as earthquakes, fire or explosions, may jeopardize the performance and safety of civil structures. Structural Health Monitoring (SHM) is nowadays a well-established technology for remote structural health and performance assessment of civil structures. The main objective of continuous SHM systems is damage detection at an early stage, so that timely countermeasures can be taken. Modal based damage detection is probably one of the most popular approaches in civil SHM, exploiting the development of several robust automated Operational Modal Analysis (OMA) algorithms in the last decades.

Modal based damage detection is very simple in principle. Defining damage as any change of the structure that adversely affects its functionality or load bearing capacity, typically associated with changes of stiffness due to cracking in concrete or masonry structures, of external and/or internal restraints, the relationship between the physical properties of the structure (i.e. mass, stiffness, damping) and its modal parameters can be  exploited. In fact, considering that changes in the physical properties induced by damage yield changes in the modal properties, the analysis of the variations of damage-sensitive features, defined in terms of modal parameters, can support remote detection of damage.

Advantages and limitations of modal based SHM are currently well established. Among the latter, the most relevant is the sensitivity of natural frequency estimates to environmental and operational variables (EOVs). Changes in natural frequency estimates due to EOVs are often of the same order of magnitude of those caused by damage. If the effect of EOVs is not taken in due consideration, type I (false identification) and type II (missed identification) errors can occur, seriously affecting the reliability of damage detection. An effective compensation of the influence of EOVs on natural frequency estimates is therefore critical in view of the development of SHM systems.

Whenever the environmental and operational influence is properly considered, modal-based SHM systems show high reliability and they give the opportunity to identify response anomalies without any prior information about damage, provided that reference monitoring data associated with the healthy condition of the structure are available.

The School of Engineering Tower in Naples is part of a building complex designed by Luigi Cosenza in a way that a typological continuity with the blocks of preexisting public housing buildings designed in 1949 is observed. It consists of an 11-storey reinforced concrete frame structure built during the 1960s. The building dimensions in plan are approximately 60 m x 80 m from the ground to the third floor; at the upper floors the dimensions in plan are about 20 m x 80 m. The building plan is also characterized by a staircase, located approximately at one third of the larger dimension, and by a slight rotation (about 4°) of this smaller portion of the plan with respect to the remaining part.

The building has been recently equipped by S2X with a continuous, vibration-based SHM system aimed at timely detect possible structural anomalies induced by the frequent earthquakes occurring in the area due to bradyseism. The SHM system consists of fifteen accelerometers with the following technical features: 10 V/g sensitivity, ±0.5 g full-scale range. Twelve accelerometers have been installed in couples at opposite corners of the building plan at levels 3, 7 and 11 and along two orthogonal directions in order to ensure the observability of the fundamental bending and torsion modes. The remaining three accelerometers have been installed in triaxial configuration at the basement of the building, and they are aimed at recording possible seismic inputs. The sensors have been wired to a 24-bit data acquisition system. Vibration data are continuously collected and automatically processed by an industrial fanless computer, which has been installed into a rack at the basement. Data acquisition and storage is managed by S2-DDA, while the automatic estimation and monitoring of the modal parameters of the monitored structure is carried out by S2-SHM.

The 1800 sec long acceleration records of the ambient vibration response of the building are continuously acquired at a sampling frequency of 100 Hz, and they are stored in distinct files. Each new file is automatically loaded and processed to extract the fundamental modal properties of the building. Thus, every thirty minutes new estimates of the fundamental modal properties of the structure are automatically extracted from the measured acceleration time series by the S2-SHM software, which also shows the time series of the identified modal properties and can be used to compensate the environmental influence and for anomaly detection. In addition to continuous data acquisition, a threshold-based data acquisition has been set by S2-DDA to store data related to possible seismic events in separate files.

The fundamental modes of the structure are listed in Table 1.

The vibration-based SHM system of the School of Engineering Main Building started operating on July 12^th, 2024. Here the results in the period between November 4^th, 2024 and March 5^th, 2025 are considered, characterized only by a single major interruption in the period between December 17^th and December 18^th, 2024, due to the need of performing some planned maintenance operations. Results of continuous monitoring in terms of natural frequency and modal damping ratio time series for the three fundamental modes are shown in the following figure.

The plots in figure 2 allow to recognize a significant environmental and operational influence on the natural frequencies and, to some extent, on the associated modal damping ratios. In addition, the occurrence of seismic events in the area, whose effects on the structural response were also recorded by the SHM system, is remarked by the red dashed lines in the same figure. The monitored structure, indeed, is located in the area of Campi Flegrei, which has been hit by several small or moderate earthquakes over the past months as a result of bradyseism. Thus, particular attention has been devoted in this study to the analysis of the patterns of natural frequencies to discriminate between environmental and operational effects, on one hand, and the possible effects of seismic input, on the other hand. Localized drops in the natural frequency time series corresponding at the occurrence of an earthquake are the first indication of a possible structural damage. However, looking at the natural frequency time series in Fig. 2 across the main seismic events (M_D>3.0) occurred in the area of Campi Flegrei during the monitoring period, it is possible to recognize that there were no clear drops caused by the earthquake loadings. However, environmental and operational variables can hide minor damage effects. Thus, a more accurate anomaly detection has been carried out by applying the Principal Component Analysis (PCA) to compensate for those effects and detect possible anomalies in the structural response.

PCA is a linear technique for SHM data normalization mapping data from their original space into a new set of coordinates called principal components scores. PCA aims at projecting the original data in the principal components space and then remap only the principal components associated with the largest variability within the data back to the original space. The reverse projection allows computing the difference between the original data and reconstructed data. In particular, the L2-norm of the residuals is here considered as the novelty index (NI). With a training period spanning between November 4^th, 2024 and January 31^st, 2025, the threshold for anomaly detection has been set considering a 5% probability of exceedance of the NI in the training period. The NI time history after the training period is shown in Fig. 3. The results show that, apart from a few outliers overcoming the threshold, no significant changes in the structural response occurred as a result of the earthquakes which hit the structure. This is consistent with the results of visual survey and inspections carried out on the structure.

Data acquisition is managed by the S2-DDA software application (Software Solution – Dynamic Data Acquisition), while automatic data processing is performed using the S2-SHM software (Software Solution – Structural Health Monitoring).