Identifikasi Parameter Modal Model Bangunan Dua Lantai Menggunakan Metode Covariance-driven Stochastic Subspace Identification

The modal parameters identification is a crucial part for designing and monitoring of a structure. This research is aimed to identify natural frequency and damping ratio of a lab-scaled two-story building model as a structure-under-test (SUT). The identification applies an operational modal analysis (OMA) technique, leveraging an algorithm of covariance-driven stochastic subspace identification (SSI-Cov) within PyOMA2 libraries. The SUT is subjected to random excitations using pseudo random signals within 0.1-25 Hz frequency range. The acceleration responses were sampled at 7.5 ms rate for 1 minute at each floor. Consequently, two modes with frequencies 2.2384 Hz and 5.9220 Hz are successfully identified below 25 Hz. These two modes yield 0.0135 and 0.0069 of damping ratios, respectively. These findings are compared to those of other algorithms that demonstrated a satisfactory identification of natural frequencies. However, a significant difference emerges in the identified damping ratios, particularly with regard to the second mode.