Maximum Likelihood Estimation of Modal Parameters in Structures Using the Expectation Maximization Algorithm

This paper presents a time-domain stochastic system identification method based on Maximum Likelihood Estimation (MLE) with the Expectation Maximization (EM) algorithm. The effectiveness of this structural identification method is evaluated through numerical simulation in the context of the ASCE benchmark problem on structural health monitoring. Modal parameters (eigenfrequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using both Stochastic Subspace Identification (SSI) method and the proposed MLE+EM method. The numerical results show that the proposed method estimates more accurate modal parameters than SSI in the presence of 10% measurement noise. Finally, adventages and disadventages of the method have been discussed.