Cumulant Based Modal Parameter Extraction of Structures

Abstract

This paper describes a nonlinear deterministic estimator based on cumulants for the extraction of modal parameters. The signal analysed is composed of multiple exponentially damped real sinusoids in unknown additive noise. Cumulants reduce significantly the effects of noise and are also an efficient way of compressing the sampled data. In modal analysis a sensor may be unable to detect some modes of vibration due to its location. Cumulants estimated from real data sampled at different locations and instances are added directly together. This average cumulant function will contain the eigenvalues for all excited modes of vibration. Finding the frequencies and corresponding damping factors is therefore reduced to solving a single average cumulant function. The performance of the proposed estimator is examined and compared with the Eigensystem Realization Algorithm via simulations.