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Application of Composite Spectrum in Steam Turbo-Generator Set
Keri Elbhbah1, Jyoti K. Sinha1, W. Hahn2, G. Tasker2
1School of Mechanical, Aerospace and Civil Engineering. The University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
2West Burton Power Station, EDF Energy, Retford, Nottinghamshire DN22 9BL, UK.
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AbstractComposite spectrum and composite bispectrum techniques have been recently developed for identifying fault(s) in rotating machines. The fusion of the measured vibration dataat all the machine bearings in the frequency domain is usedto construct sucha composite spectrum and composite bispectrum for the representation of the entire machine. These…………... The observations and results of the current study also indicate the presence of localised misalignment and suspected rotating stall in the composite spectrum.
Key wordsRotating Machines, Condition Monitoring, Spectrum, Data Fusion, Composite Spectrum.
1.0 Introduction
West Burtonpower plant is a plant owned by EDF Company and consists of 4 steam (TG) units for power generation. Each TG unit consists of a High Pressure (HP) turbine, an Intermediate Pressure (IP) turbine, and three Low Pressure (LP) turbines, together with a generator and an exciter. The schematic of the TG set consisting of 14 journal bearings are shown in Figure 1.
Figure 1 Schematic diagram of Turbo generator set
Vibration based diagnosis often requires vibration measurements on all bearing pedestals in both horizontal and vertical directions for the fault diagnosis. Such measurement approach is ……………indicates the possibility of rotor stall, for which the LP turbines seem to be the source [1]. This effect is not seen on the HP, IP and the generator bearings.
Recently, data fusion ……..data from all bearings [2]. The composite ………on a small experimental rotating rig [3]. This is expected to simplify the condition monitoring procedure and fault diagnosis process. This technique is ………………observations and the results are discussed in the paper.
2.0 Spectrum
The conventional power spectrum density (PSD) …………………..of the signal as;
PSD, , k = 1, 2, 3, …, N(1)
Where, is the power density, is the DFT at frequency for the time series and is its complex conjugate. N is the number of the frequency points. E[ ] denotes the mean operator, here it means that the PSD is the averaged spectrum over a time length of the signal, say, t.
2.1 Spectrum analysis [1]
Typical measured amplitude spectra at bearing 4 ………………………is deliberately kept, as it is expected that the rotor well self-align during operation.
Similarly, the measured spectra at …………………….any indication of this phenomenon.
Figure 2 Typical amplitude spectra at bearing 4
Figure 3 Typical amplitude spectra at bearing 11
Figure 4 Typical amplitude spectra at 3000 RPM, a-Bearing 5, b-Bearing 6, c-Bearing 7, d-Bearing 8
3. Composite Spectrum
The composite spectrum is ………………for all the bearings and the composite spectrum is calculated as [3];
(2)
Where,is called the Composite Fourier Transformation…………… conjugate.is computed as;
(3)
Where, is the Cross-power Spectral Density (CSD) between the two signals andcollected at two bearings. It is also computed by using the
Discrete Fourier transform (DFT) of these signals as;
CSD, (4)
Where, is the ordinary coherence [4] between two signals averaged over the time length.
3.1 Composite Spectrum Analysis
Composite spectrum (CS) has been computed for the measured vibration data from ………………………the composite spectrum is capable of identifying the local defects.
4.0 Conclusion
Data fusion (composite spectrum) proposed…………… compared to the adopted practice in the vibration-based diagnosis in rotating machines.
References
[1] Sinha, J.K., Hahn, W., Elbhbah, K., Tasker, G., and 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.
[2] Sinha, J.K., and Elbhbah, K., 2013. A Future Possibility of Vibration based Condition Monitoring of rotating machines. Mechanical Systems and Signal Processing (MSSP), 34 (2013), pp. 231–240.
[3] Elbhbah, K., and Sinha, J.K., 2013. Vibration-based Condition Monitoring of Rotating Machines using a Machine Composite Spectrum. Journal of Sound and Vibration, (JSV), 332(2013), pp. 2831-2845.
[4] Ewins, D.J., 2000. Modal Testing–Theory, Practice and Application. Research Studies Press, UK, 2nd Edition.
Authors’ Biography
Passport size photo / Keri ElbhbahDr Keri Elbhbah is Knowledge Transfer Partnership (KTP) Associate, School of MACE, The University of Manchester, UK and currently based in EDF West Burton Power Station, Retford, UK. Dr Elbhbah is doing project on vibration-based blade health monitoring of steam turbines.
Passport size photo / Jyoti K. Sinha
Dr Jyoti K. Sinhais Programme Director, Reliability Engineering and Asset Management MSc and Head, Dynamics Laboratory, School of Mechanical, Aerospace and Civil Engineering. The University of Manchester, Manchester, M13 9PL, UK. Dr Sinha is involved in and solved a number of industrially applied research projects related to Vibration-based Condition Monitoring and Maintenance of Machines and Structures in last 26 years. Dr Sinha is the author of more than 60 technical reports, nearly 150 technical papers (Journals and conferences) and gave a number of keynote/invited lectures. Dr Sinha is also the associate editor of two international journals,Structural HealthMonitoring: An International JournalandJournal of Vibration Engineering and Technologies, editorial board member of the journalStructural Monitoring and Maintenance, author of a book “Vibration Analysis, Instruments and Signal Processing” and co-author of two books. He is also technical committee member of IFTOMM Rotordynamics.