Blind separation of structural modes by compact-bandwidth regularization - Wang, Li; Huang, Min; Lu, Zhong-Rong (Mechanical systems and signal processing, 2019)
•A new compact-bandwidth regularization approach is proposed within the signal processing framework for operational modal analysis.•The key idea behind the proposed approach is that an arbitrary mode is compact in the frequency domain.•The spectrum-peak-based rule is proposed for choice of initial modal parameters.•The L-curve method along with a derived bound is used for regularization parameter estimation.•Results shown the effectiveness of the proposed approach for various types of excitations and the case with closely spaced modes. Operational modal analysis (OMA) has received tremendous interest from engineering fields in recent years. This paper develops a compact-bandwidth regularization approach for OMA within the signal processing framework. The key ingredient lies in the fact that a structural mode is always compact in the frequency domain and this results in the compact-bandwidth constraint for structural modes. To implicitly enforce the compact-bandwidth constraint, the compact-bandwidth regularization is introduced to conventional blind modal separation. Then, the alternating minimization algorithm is used to iteratively get the solution in the immediately-at-once or one-by-one manner. In proceeding so, the spectrum-peak-based rule is adopted for choice of initial modal parameters and the L-curve method in conjunction with a theoretically derived bound is applied to estimate a proper regularization parameter. Numerical examples and an experimental test case are studied along with comparison to some usual OMA approaches to see the performance and advantages of the proposed approach in modal identification.