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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....
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Published in: | Mechanical systems and signal processing 2007-11, Vol.21 (8), p.3072-3087 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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. |
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ISSN: | 0888-3270 1096-1216 |
DOI: | 10.1016/j.ymssp.2007.05.007 |