Accurate measurement of the dynamic parameters of viscoelastic materials is crucial for vibration and acoustic performance prediction. However, inverse parameter identification via Frequency Response Functions (FRFs) faces increasing difficulties at higher frequencies, primarily due to the inherent numerical instability of classical modal-function-based FRF models, which restricts their use to low-order modes. This study presents an enhanced inverse identification method for determining the high-frequency-dependent shear modulus and loss factor of viscoelastic sandwich beams. The core contribution is an improved FRF model, where the conventional divergent modal function is replaced by a stable, Fourier-series-based analytical formulation. This key modification overcomes computational limitations, enabling stable and accurate high-frequency parameter identification. The method integrates this advanced model with an optimization algorithm and is validated through multi-point impact tests, demonstrating a significant extension of the identifiable frequency range with maintained efficiency. This work provides a stable, accurate, and practical tool for high-frequency inverse characterization of viscoelastic materials, essential for advanced damping design.
Wang et al. (Mon,) studied this question.