Automation of the stabilization diagrams for subspace based system identification

For the continuous real-time monitoring of structures, the realization of a fully automatic real time system identification without any human intervention is the most crucial step. In this study, a new technique for the automation of the stability diagrams is developed that uses the modal phase collinearity (MPC) in order to quantify the spatial consistency of the identification results. In the new technique, the stabilization diagram is modeled as a histogram composed of overlapping bins. New strategies for the multiple occurrence of poles in the neighboring bins and double poles within a bin are developed. A new cluster validity index is proposed which can solve the problem caused by the scale of measurements and which can be directly calculated from non-normalized data. The threshold limits are defined for the proposed index. The results of the study show that the automation of the pole selection process from the stabilization diagrams is successfully realized. It is also shown that for local modes, the MPC value will be substantially smaller as compared to the global modes and can be used as a quick, efficient and powerful measure of global versus local response behavior.