Blind source separation based vibration mode identification

In this paper, a novel method for linear normal mode (LNM) identification based on blind source separation (BSS) is introduced. Modal coordinates are considered as a specific case of sources that have certain time structure. This structure makes modal coordinates identifiable by many BSS algorithms. However, algorithms based on second-order statistics are particularly suited for extracting LNMs of a vibration system. Two well-known BSS algorithms are considered. First, algorithm for multiple unknown signals extraction (AMUSE) is used to illustrate the similarity with Ibrahim time domain (ITD) modal identification method. Second, second order blind identification (SOBI) is used to demonstrate noise robustness of BSS-based mode shape extraction. Numerical simulations and experimental results from these BSS algorithms and ITD method are presented.