Abstract
Laborelec is responsible for the follow-up of the vibration behavior of a fleet of more than 100 shaft lines within the power generation division of GDF SUEZ. Vector vibration monitoring of such a large number of units permits to develop a detailed comparison of the vibration behavior of units of a similar type. Nowadays, an important part of that fleet consists of combined-cycle single shaft units. Spiral vibrations, as described already in extensive reference papers (Schmied, Proceedings of the ASME conference on rotating machinery dynamics, 1987; Pennacchi et al. Proceedings of the ISMA conference noise and vibration engineering, 2010; Eckert et al. 7th IFToMM conference on rotor dynamics, 2006; Eckert and Schmied, J Eng Gas Turbines Power 130:012509, 2008) have been measured on a large part of this single shaft fleet, for some even already since commissioning. Due to continuous vector vibration monitoring and extensive measurement campaigns in order to better understand the driving influences behind this phenomenon, a large reference database is available to describe the observed differences of this hot spot behavior (period, modal deformation, limit cycle,…). Although these shaft lines can be considered as identical from a macro-scale point of view, quite various dynamic responses have been measured over the years. In this way, an alternative and interesting image can be sketched of this spiral vibration behavior on large turbomachinery equipment from an operational point of view. This paper will therefore describe the similarities, differences and learning points from specific vibration analysis together with recent field experiences on spiral vibrations measured on single shaft units within the GDF SUEZ fleet.
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References
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© 2015 Springer International Publishing Switzerland
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Matthys, K., Schmied, J. (2015). Similarity Analysis of Spiral Vibration Behavior on Large Turbomachinery Shaft Lines. 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_185
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DOI: https://doi.org/10.1007/978-3-319-06590-8_185
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