Title: Localization of the blade excitation using shaft vibration signal measurement
Authors: Vašíček, Vojtěch
Liška, Jindřich
Jakl, Jan
Strnad, Jaromír
Citation: VAŠÍČEK, V. LIŠKA, J. JAKL, J. STRNAD, J. Localization of the blade excitation using shaft vibration signal measurement. In Proceedings of CM 2022. London: The British Institute for Non-Destructive Testing, 2022. s. 121-130. ISBN: 978-1-71386-227-7
Issue Date: 2022
Publisher: The British Institute for Non-Destructive Testing
Document type: konferenční příspěvek
ConferenceObject
URI: 2-s2.0-85145873842
http://hdl.handle.net/11025/51442
ISBN: 978-1-71386-227-7
Keywords in different language: Blade vibration;Shaft vibration;Localization;Signal processing
Abstract in different language: Condition monitoring is the process of signal measuring and processing to detect an early change in the system. In turbomachinery, blade state monitoring is an important task of this kind. It is important, especially in terms of the last stages of the low-pressure turbine. In general, the stress acting on blades here is the highest. In recent years, the authors of this paper developed a new approach to low-pressure steam turbine blades monitoring using the standard instrumentation by the shaft vibration sensors. This approach is described in this paper together with examples of experimental data evaluation. Apart from amplitudes and frequencies of the blade vibration, it was also shown that the phase spectrum can be used for the localization of blade excitation. This approach is described in this paper in detail. The derived formulas describing the principle were validated by the measurements using the experimental rotor stand in the laboratory.
Rights: Plný text není přístupný.
© 18th International Conference on Condition Monitoring and Asset Management, CM 2022.
Appears in Collections:Konferenční příspěvky / Conference papers (NTIS)
Konferenční příspěvky / Conference Papers (KKY)
OBD

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/51442

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