A methodology for vibro-acoustical Operational Modal Analysis of microsystems

The need for tools to understand, test, model, and predict microsystems performances inspires the wide framework of multidisciplinary research on MEMS sensor technologies. In this work, to dynamically identify these systems, we propose a particular output-only modal analysis (OMA) methodology that includes acoustical excitation via speakers and response measurements through a laser Doppler vibrometer and a microphone. Specifically, we account for the fluid- structure coupling relying on the analytical modal model of the cross-power spectra (CPs) between the structural and the acoustical system outputs, and we apply modal parameter estimation (MPE) techniques from the OMA field. The effectiveness of the methodology is illustrated through the in-plane and out-of-plane flexural mode experimental identification of a high-quality factor quartz tuning fork (QTF), immersed in a fluid environment. This device exhibits a dominant diffusive-velocity contribution in the description of the overall forces exerted by the fluid and, from this point of view, significantly differs from the typical structures analyzed via OMA, where the main effect of the interaction is viscous damping. We point out that the acoustical pressure measurement can be used as a robust reference, instead of the commonly used structural sensors. It results useful for MEMS where, in general, external exciting or measurement components adversely impact the analysis, altering the values of dynamic parameters. In this sense, the use of the vibro-acoustical OMA framework produces a simple and effective methodology for microsystems' identification.

Automated summary

This work proposes an output-only modal analysis (OMA) methodology for dynamically identifying microsystems. By considering the fluid-structure coupling and using modal parameter estimation (MPE) techniques, the effectiveness of the methodology is demonstrated. This approach is useful for research and analysis in MEMS sensor technologies.