Merging and rescaling sensor data for accurate structural health assessment of 3D truss structures using structural software

Purpose This study presents a comprehensive approach for assessing the structural health of a 3D truss structure. By merging and rescaling sensor data from multiple setups, frequency domain decomposition (FDD) is applied to extract natural frequencies and modal shapes. These experimental results are compared with theoretical values obtained from a 3D finite element model created using structural software. Design/methodology/approach A MATLAB code was developed to implement FDD, enabling the analysis of sensor data. The results from the developed FDD code were validated against those from the ERA method, demonstrating accuracy and reliability. A finite element model was created using Etabs software and compared with experimental results. While minor discrepancies were observed due to factors like joint mass and member thickness variations, the overall agreement between theoretical and experimental modal properties was satisfactory. Findings The findings of this study demonstrate the effectiveness of the proposed approach in assessing structural health and validating the finite element model. The developed FDD code is shown to be accurate and reliable, and the comparison between experimental and theoretical results highlights potential areas for model improvement. Originality/value This study provides a valuable methodology for structural health monitoring and finite element model correlation, contributing to the understanding and maintenance of complex truss structures.