New figures of merit for non-modal test analysis correlation

The use of antiresonances in test-analysis correlation and dynamic model updating is considered in this paper. Antiresonances are not independent from modal data, and the related information is alternative and not additional to modal information. Several reasons exist to prefer antiresonances to mode shapes. First, antiresonances are quite important in deciding whether analytical and experimental FRFs are well correlated or not. Furthermore, antiresonances can be easily computed from the FE model, and identified from experimental FRFs with much less error than mode shapes. Two procedures for dynamic model updating are considered: one based on inverse sensitivity, and a second one based on multiobjective optimization. Problems connected with using antiresonances of transfer FRFs, as opposed to drive point FRFs, are also highlighted. Numerical results show that both the inverse sensitivity and the optimization approach work well with drive point FRFs.