Abstract Summary
Quantification of statistical errors in modal parameter estimates is a topic of intense interest in operational modal analysis, damage diagnosis, modal updating, among many other engineering fields. The uncertainty in the modal parameter estimates stems from the finite data length, unknown, or partly measured inputs, the choice of the identification algorithm, the sensor layout, among other factors. This paper proposes a sensor placement strategy that yields an optimal design of the sensor layout for minimizing the uncertainty when the modal parameters of the structure are obtained from data. The optimization criterion is based on the Fisher information contained in the modal parameter estimates. The related uncertainty is obtained with statistical delta method, which is coupled with subspace identification for modal parameter estimation. The performance of the proposed approach is illustrated on an extensive Monte Carlo simulation of a mechanical system.
