PSI - Issue 78

Antonio Sánchez López-Cuervo et al. / Procedia Structural Integrity 78 (2026) 1791–1798

1792

ϕ i Mode shape of the i -th mode identified from the experimental data ϕ i Mode shape of the i -th mode obtained from the numerical model ϕ H i Hermitian transpose (conjugate transpose) of the mode shape ϕ i k M k Bending sti ff ness of the column-slab joint in intermediate levels about the k -axis k ′ M k Bending sti ff ness of the column-slab joint in top columns about the k -axis k ′′ M k Bending sti ff ness of the column-slab joint in bottom columns about the k -axis U k Support sti ff ness in the k -direction α Weight assigned to the frequency error term in the objective function β Weight assigned to the mode shape error term in the objective function

a aver Weight for the average frequency error component a max Weight for the maximum frequency error component b aver Weight for the average mode shape error component b max Weight for the maximum mode shape error component

1. Introduction

Following a catastrophic event, such as an earthquake, it is essential to perform a rapid and accurate assessment of the structural health of buildings and infrastructure to ensure public safety, prioritize the reoccupation of critical facilities, and allocate inspection and repair resources e ffi ciently. In this context, SHM systems play a key role, as they facilitate the remote and near real-time evaluation of structural condition, minimizing personnel exposure and accelerating post-seismic response (C¸ elebi, 2019). Among the most widely used SHM techniques is the identification of vibrational properties through OMA tech niques, typically based on acceleration time histories (Magalha˜es et al., 2008, 2012). OMA enables the identification of modal parameters, such as natural frequencies and mode shapes, which are sensitive to the presence of damage. However, accurate localization and quantification of damage using this approach generally require dense sensor net works and high-quality measurements (Limongelli, 2019; Anastasopoulos and Reynders, 2025). As a complementary solution, strain-based sensors such as SGs can also be used for the monitoring of vibrational properties. In addition to providing redundancy in the identification of frequencies—thus reducing associated uncer tainties—these sensors allow for the identification of mode shapes in terms of strain, which have been shown to be more sensitive to structural damage than displacement-based mode shapes (Reynders et al., 2007; Anastasopoulos et al., 2019; Anastasopoulos, 2020). Therefore, integrating accelerometers and strain sensors for the identification of dynamic properties is of great in terest, as it enables the extraction of a greater number of modal parameters, improves the robustness of the monitoring system, and increases the reliability of damage assessment (Kralovec and Schagerl, 2020). The objective of this study is to evaluate the potential of vibration-based monitoring systems integrating data obtained from accelerometers and SGs for the detection and characterization of structural damage in a laboratory scale steel frame. To this end, the evolution of modal properties identified through OMA is analysed across di ff erent progressive damage scenarios. Additionally, a FEM of the structure is updated using a multi-objective optimization approach, based on the modal properties identified by both sensing systems. The remainder of this paper is organised as follows: Section 2 describes the steel frame, the damage scenarios, and the formulation of the multi-objective optimization problem. Section 3 presents the e ff ect of damage on modal properties and the results of the model calibration. Finally, Section 4 summarizes the main findings of the study.

2. Methodology

2.1. Test structure

The structure under investigation consists of a five-story steel frame with rigid joints and a total height of 1.40 m (0.28 m per story), as illustrated in Fig. 1(a).