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Experimental Estimation of Speed-Dependent Active Magnetic Bearing Rotordynamic Parameters

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Proceedings of the 9th IFToMM International Conference on Rotor Dynamics

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 21))

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Abstract

Modern high-speed and high-power flexible rotors are increasingly supported on active magnetic bearings (AMBs). Apart from supporting/attenuating rotors now AMBs have been utilized for obtaining fault conditions of such rotating machineries. For this accurate characterization of AMB rotordynamic parameters is very important apart from accurate modeling of rotors. The latter could be performed by finite element methods quite accurately. The present paper proposes a model based identification algorithm that concurrently estimates the speed-dependent AMB rotordynamic parameters and residual unbalances present in a flexible rotor system that is fully levitated on AMBs. To test this algorithm, an experiment on a flexible rotor system fully levitated on active magnetic bearings (AMBs) by PID controllers, was conducted. The rotor was given the run-up and run-down within certain duration of time for the fast, medium and slow runs. For each run displacements at all disc locations and currents at AMB locations were collected. By using these responses, simultaneously the speed-dependent bearing parameters and residual unbalances were estimated using the developed identification algorithm. The estimates were consistent for different runs and compare well with theoretical values.

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Acknowledgments

Authors acknowledge Prof. R. Markert and Dr. F. Dohnal of Technical University of Darmstadt (TUD), Germany for the experimental data used in the present work.

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Correspondence to Rajiv Tiwari .

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© 2015 Springer International Publishing Switzerland

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Tiwari, R., Viswanadh, T. (2015). Experimental Estimation of Speed-Dependent Active Magnetic Bearing Rotordynamic Parameters. In: Pennacchi, P. (eds) Proceedings of the 9th IFToMM International Conference on Rotor Dynamics. Mechanisms and Machine Science, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-319-06590-8_117

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  • DOI: https://doi.org/10.1007/978-3-319-06590-8_117

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06589-2

  • Online ISBN: 978-3-319-06590-8

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