Combination of operational modal analysis algorithms to identify modal parameters of an actual centrifugal compressor

TL;DR

This paper introduces a statistical method to combine estimates from various Operational Modal Analysis algorithms, improving accuracy and uncertainty quantification of modal parameters in centrifugal compressors.

Contribution

It proposes a novel statistical procedure to integrate multiple OMA algorithm outputs and derive joint probability distributions for modal parameters.

Findings

Combined OMA algorithms yield accurate modal parameters.

The method provides reliable uncertainty estimates.

Low computational cost for the proposed strategy.

Abstract

The novelty of the current work is precisely to propose a statistical procedure to combine estimates of the modal parameters provided by any set of Operational Modal Analysis (OMA) algorithms so as to avoid preference for a particular one and also to derive an approximate joint probability distribution of the modal parameters, from which engineering statistics of interest such as mean value and variance are readily provided. The effectiveness of the proposed strategy is assessed considering measured data from an actual centrifugal compressor. The statistics obtained for both forward and backward modal parameters are finally compared against modal parameters identified during standard stability verification testing (SVT) of centrifugal compressors prior to shipment, using classical Experimental Modal Analysis (EMA) algorithms. The current work demonstrates that combination of OMA algorithms can provide quite accurate estimates for both the modal parameters and the associated uncertainties with low computational costs.