Influence of the number of sensors in the modal parameter estimation and damage detection using Operational Modal Analysis

Structural Health Monitoring (SHM) based on dynamic techniques relies on accurate identification of modal parameters to assess structural integrity. This study investigates the impact of the number of sensors on the estimation of natural frequencies, damping ratios and mode shapes, as well as on the ability to detect damage. The experimental work is conducted on a four-story laboratory-scale shear building model. Damage is introduced in a controlled manner by varying the mass of each floor slab, simulating changes in service conditions. Operational Modal Analysis (OMA) under ambient excitation is employed to identify modal parameters across different scenarios and sensor configurations. Several layouts are considered to evaluate how reducing the number of sensors affects both modal identification accuracy and sensitivity to structural changes. Results indicate that natural frequencies remain relatively robust under sparse instrumentation, whereas mode shapes and damping ratio estimations degrade significantly, impacting the effectiveness of damage indices based on modal correlation. This work provides practical guidelines for optimizing structural monitoring systems, balancing cost and reliability. The results are promising for real-world applications where full instrumentation is often impractical, such as bridges, buildings and wind towers. Furthermore, implications for predictive maintenance strategies and the deployment of SHM systems in constrained environments are discussed.