Detection of structural abnormality of industrial rotary machine using DRS-aided operational modal analysis

Abstract One of the important issues concerning the dynamic analysis of rotating machines is the separation of deterministic and random components. In industrial conditions, the determination of dynamic parameters is performed using Operational Modal Analysis (OMA). In order to correctly identify the natural frequencies, it is necessary to separate the components associated with them from rotational speed harmonics. The presented article shows the application of in-operational measurements with a new data pre-processing procedure for OMA carried out on a rotating machine operating in a large industrial plant. An innovative procedure for removing harmonics from Cross-Power Spectral Density (CSD) was used in the data preparation process. The novel aspect in the paper is the application of the Discrete Random Separation (DRS) algorithm to remove harmonics from data for OMA. A procedure for the synchronous use of DRS for multiple time histories has been developed so that modal analysis is possible.