This paper investigates the use of conventional operational modal analysis (OMA) techniques for modal parameters identification of a rotating system supported by roller bearings. Although largely applied in civil engineering, in-depth studies on different types of systems are still limited in the literature. The novel of the paper is to address such issue by applying conventional OMA methods, such as enhanced frequency domain decomposition (EFDD) and stochastic subspace identification (SSI-data), to identify the modal parameters of a rotating machine, investigating the challenging particularities of these systems due to their inherent operating conditions, especially regarding the presence of harmonic forces, eventually closed-spaced modes, and non-proportional damping due to the bearings. The results presented in the experimental tests showed that, with the use of specific tools, in comparison with traditional experimental modal analysis (EMA), the used OMA methods have managed to successfully identify the modal parameters of a roller bearing supported rotor.
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The authors would like to thank National Council for Scientific and Technological Development — CNPq, grant # 424899/2018-3, and grants # 2015/20363-6 and # 2017/07454-8 from the São Paulo Research Foundation (FAPESP) for the financial support to this research.
Gustavo Chaves Storti is a Ph.D. student in the School of Mechanical Engineering at the University of Campinas. His current research interests include structural dynamics, Operational Modal Analysis, Rotordynamics, and Machine Learning.
Tiago Henrique Machado is an Assistant Professor at the School of Mechanical Engineering from the University of Campinas. His current research interests include Rotordynamics, Fault Diagnosis and Identification, Hydrodynamic bearings, Structural Dynamics, Experimental and Operational Modal Analysis, and Machine Learning.
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Storti, G., Machado, T. The use of operational modal analysis in the process of modal parameters identification in a rotating machine supported by roller bearings. J Mech Sci Technol 35, 471–480 (2021). https://doi.org/10.1007/s12206-021-0105-3
- Operational modal analysis
- Parameter identification
- Roller bearing
- Rotating system