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Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Online Monitoring of Thermoacoustic Eigenmodes in Annular Combustion Systems Based on a State-Space Model

[+] Author and Article Information
D. Rouwenhorst

IfTA Ingenieurbüro für Thermoakustik GmbH,
Gröbenzell 82194, Germany
e-mail: driek.rouwenhorst@ifta.com

J. Hermann

IfTA Ingenieurbüro für Thermoakustik GmbH,
Gröbenzell 82194, Germany

W. Polifke

Professur für Thermofluiddynamik
Fakultät für Machinenwesen,
Technische Universität München,
Garching 85747, Germany
e-mail: polifke@tfd.mw.tum.de

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 20, 2016; final manuscript received July 7, 2016; published online September 13, 2016. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(2), 021502 (Sep 13, 2016) (8 pages) Paper No: GTP-16-1238; doi: 10.1115/1.4034260 History: Received June 20, 2016; Revised July 07, 2016

Thermoacoustic instabilities have the potential to restrict the operability window of annular combustion systems, primarily as a result of azimuthal modes. Azimuthal acoustic modes are composed of counter-rotating wave pairs, which form traveling modes, standing modes, or combinations thereof. In this work, a monitoring strategy is proposed for annular combustors, which accounts for azimuthal mode shapes. Output-only modal identification has been adapted to retrieve azimuthal eigenmodes from surrogate data, resembling acoustic measurements on an industrial gas turbine. Online monitoring of decay rate estimates can serve as a thermoacoustic stability margin, while the recovered mode shapes contain information that can be useful for control strategies. A low-order thermoacoustic model is described, requiring multiple sensors around the circumference of the combustor annulus to assess the dynamics. This model leads to a second-order state-space representation with stochastic forcing, which is used as the model structure for the identification process. Four different identification approaches are evaluated under different assumptions, concerning noise characteristics and preprocessing of the signals. Additionally, recursive algorithms for online parameter identification are tested.

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Figures

Grahic Jump Location
Fig. 1

Sketch of an annular combustor with 1D acoustic waves F̂m and Ĝm in the combustion chamber. Premixing ducts of the burners connect the combustion chamber with the plenum.

Grahic Jump Location
Fig. 2

Section view showing the premixing duct with reference velocity ûx for the heat release model. The combustion zone is subject to the pressure fluctuations in the combustion chamber, but secluded for azimuthal particle velocity.

Grahic Jump Location
Fig. 3

Comparison of the current model with the analytic (linearized) ATACAMAC model. Eigenfrequencies and decay rates of a system with burner pattern 1212 for variable time delay τ1. Both solutions coincide very well after enforcing the same conditions, noting the small deviations around mω0τ1/2π=0.8.

Grahic Jump Location
Fig. 4

Modal peak in the power spectral density of clockwise and anticlockwise waves of the surrogate time-series data generated by Eq. (17)

Grahic Jump Location
Fig. 5

Online identified decay rates α¯1,2 of the thermoacoustic system during slow parameter variation. Theoretical decay rates α1,2 following from the prescribed parameters by Eq. (12) are given in dashed lines.

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