Polymax Plus Estimator


The motivation behind introducing the Polymax Plus modal parameter estimator was to keep the property of clear stabilization diagram constructed by the Polymax estimator (Polymax user friendliness) and at the same time to have improved, statistically optimal, modal parameter estimates (Maximum likelihood (ML) accuracy). The Polymax Plus estimator is based on the combination of the ML estimator and the classical Polymax estimator. This approach overcomes the major drawback of the currently available Polymax estimator of having a high bias on the damping estimate in the cases of very noisy data and/or weakly excited modes. Unlike the deterministic methods, the Polymax Plus estimator offers more consistent modal parameter estimates together with their uncertainty bounds, which play an important role in the model validation process. Moreover, unlike the stochastic methods, it features clear stabilization charts in a fast way. This estimator is optimized with respect to the computational time and memory requirements.

Polymax & Polymax Plus estimators applied to in-flight flutter testing data 

Polymax stabilization chart

A synthesized FRF compared to the measured one

Polymax Plus stabilization chart

Mode shape

Recently the innovative identification group is developing new estimators strategies that allow exploiting all the data information that current methods (Experimental and Modal analysis –EMA and OMA) fail to do. More specifically OMA methods do not take into account input information while EMA methods considers disturbance inputs  as  noise. The new estimators are developed int the context of maximum likelihood Estimators (MLE) taking into account the possibility and its effects when the full noise information matrix is not available. The new estimators are assessed based on the covariance of the parameters, the convergence time and its efficiency.