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Application of Composite Spectrum in Steam Turbo-Generator Set

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Vibration Engineering and Technology of Machinery

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 23))

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Abstract

Composite spectrum and composite bispectrum techniques have been recently developed for identifying fault(s) in rotating machines. The fusion of the measured vibration data at all the machine bearings in the frequency domain is used to construct such a composite spectrum and composite bispectrum for the representation of the entire machine. These techniques are now applied to a Turbo-generator (TG) set which consists of a high pressure (HP) turbine, an intermediate pressure (IP) turbine and 3 low pressure (LP) turbines in addition to an exciter and a generator. Earlier study using the spectrum analysis of the measured vibration acceleration data on the bearings of the TG set during machine normal operation indicates the possibility of the rotating stall in LP turbines and misalignment between the IP and LP rotors. The observations and results of the current study also indicate the presence of localised misalignment and suspected rotating stall in the composite spectrum.

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References

  1. Sinha JK, Hahn W, Elbhbah K, Tasker G, Ullah I (2012) Vibration investigation for low pressure turbine last stage BLADE failure in steam turbines of a power plant. ASME TurboExpo 2012, June 11–15. Copenhagen, Denmark

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  2. Sinha JK, Elbhbah K (2013) A future possibility of vibration based condition monitoring of rotating machines. Mech Syst Sig Process (MSSP) 34(2013):231–240

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  3. Elbhbah K, Sinha JK (2013) Vibration-based condition monitoring of rotating machines using a machine composite spectrum. J Sound Vib (JSV) 332(2013):2831–2845

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Correspondence to Keri Elbhbah .

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© 2015 Springer International Publishing Switzerland

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Elbhbah, K., Sinha, J.K., Hahn, W., Tasker, G. (2015). Application of Composite Spectrum in Steam Turbo-Generator Set. In: Sinha, J. (eds) Vibration Engineering and Technology of Machinery. Mechanisms and Machine Science, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-09918-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-09918-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09917-0

  • Online ISBN: 978-3-319-09918-7

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