Research Papers: Gas Turbines: Structures and Dynamics

Efficient Generation of Engine Representative Tip Timing Data Based on a Reduced Order Model for Bladed Rotors

[+] Author and Article Information
Felix Figaschewsky

Chair of Structural Mechanics and
Vehicle Vibration Technology,
Brandenburg University of Technology
Cottbus D-03046, Germany
e-mail: felix.figaschewsky@b-tu.de

Benjamin Hanschke

Chair of Structural Mechanics and
Vehicle Vibration Technology,
Brandenburg University of Technology
Cottbus D-03046, Germany
e-mail: benjamin.hanschke@b-tu.de

Arnold Kühhorn

Chair of Structural Mechanics and
Vehicle Vibration Technology,
Brandenburg University of Technology
Cottbus D-03046, Germany
e-mail: kuehhorn@b-tu.de

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 25, 2018; final manuscript received June 28, 2018; published online November 14, 2018. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 141(1), 012503 (Nov 14, 2018) (9 pages) Paper No: GTP-18-1339; doi: 10.1115/1.4040748 History: Received June 25, 2018; Revised June 28, 2018

In modern compressors, the assessment of blade vibration levels as well as health monitoring of the components are fundamental tasks. Traditionally, this assessment is done by the application of strain gauges (SG) to some blades of the assembly. In contrast to SGs, blade tip timing (BTT) offers a contactless monitoring of all blades of a rotor and there is no need of a telemetry system. A major issue in the interpretation of BTT data is the heavily undersampled nature of the signal. Usually, newly developed BTT algorithms are tested with sample data created by simplified structural models neglecting many of the uncertainties and disturbing influences of real applications. This work focuses on the creation of simulated BTT datasets as close as possible to real case measurements. For this purpose, a subset of nominal system modes (SNM) representation of a compressor rotor is utilized. This model is able to include a large number of features present in real measurements, such as mistuning, static blade deflections due to centrifugal loads, aerodynamic damping, and multiple mode resonances. Additionally, manufacturing deviations of the blade geometry, probe positioning errors (PPEs) in the BTT system, and noise in the time of arrivals (TOAs) are captured by the BTT simulation environment. The main advantage of the created data is the possibility to steadily increase the signal complexity. Starting with a “perfect” signal the simulation environment is able to add different uncertainties one after the other. This allows the assessment of the influence of different features occurring in real measurements on the performance and accuracy of the analysis algorithms. Finally, a comparison of simulated BTT data and real data acquired from a rig test is shown to validate the presented approach of BTT data generation.

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Heath, S. , and Imregun, M. , 1997, “ A Review of Analysis Techniques for Blade Tip-Timing Measurements,” ASME Paper No. 97-GT-213.
Beirow, B. , Kühhorn, A. , and Nipkau, J. , 2009, “ On the Influence of Strain Gauge Instrumentation on Blade Vibrations of Integral Blisk Compressor Rotors Applying a Discrete Model,” ASME Paper No. GT2009-59207.
Vercoutter, A. , Berthillier, M. , Talon, A. , Burgardt, B. , and Lardiès, J. , 2012, “ Estimation of Turbomachinery Blade Vibrations From Tip-Timing Data,” 10th International Conference on Vibrations in Rotating Machinery, London, Sept. 11–13, pp. 233–245.
Carrington, I. B. , Wright, J. R. , Cooper, J. E. , and Dimitriadis, G. , 2001, “ A Comparison of Blade Tip Timing Data Analysis Methods,” Proc. Inst. Mech. Eng., Part G, 215(5), pp. 301–312. [CrossRef]
Schlagwein, G. , and Schaber, U. , 2006, “ Non-Contact Blade Vibration Measurement Analysis Using a Multi-Degree-of-Freedom Model,” Proc. Inst. Mech. Eng., Part A, 220(6), pp. 611–618. [CrossRef]
Kharyton, V. , Laine, J.-P. , Thouverez, F. , and Kucher, O. , 2010, “ Simulation of Tip-Timing Measurements of a Cracked Bladed Disk Forced Response,” ASME Paper No. GT2010-22388.
Salhi, B. , Berthillier, M. , Lardiès, J. , Voinis, P. , and Bodel, C. , 2007, “ A Subspace Method for Modal Identification of Bladed Assemblies Using Blade Tip Timing Data,” ASME Paper No. GT2007-28151.
Stéphan, C. , Berthillier, M. , Lardiès, J. , and Talon, A. , 2008, “ Tip Timing Data Analysis for Mistuned Bladed Discs Assemblies,” ASME Paper No. GT2008-50825.
Gallego-Garrido, J. , Dimitriadis, G. , and Wright, J. R. , 2007, “ A Class of Methods for the Analysis of Blade Tip Timing Data From Bladed Assemblies Undergoing Simultaneous Resonances—Part I: Theoretical Development,” Int. J. Rotating Mach., 2007, p. 27247.
Diamond, D. H. , Heyns, P. S. , and Oberholster, A. J. , 2015, “ A Comparison Between Three Blade Tip Timing Algorithms for Estimating Synchronous Turbomachine Blade Vibration,” Ninth WCEAM Research Papers, Springer, Cham, Switzerland, pp. 215–225.
Heath, S. , and Imregun, M. , 1996, “ An Improved Single-Parameter Tip-Timing Method for Turbomachinery Blade Vibration Measurements Using Optical Laser Probes,” Int. J. Mech. Sci., 38(10), pp. 1047–1058. [CrossRef]
Yang, M. T. , and Griffin, J. H. , 2001, “ A Reduced-Order Model of Mistuning Using a Subset of Nominal System Modes,” ASME J. Eng. Gas Turbines Power, 123(4), pp. 893–900. [CrossRef]
Giersch, T. , Hönisch, P. , Beirow, B. , and Kühhorn, A. , 2013, “ Forced Response Analyses of Mistuned Radial Inflow Turbines,” ASME J. Turbomach., 135(3), p. 031034.
Figaschewsky, F. , Kühhorn, A. , Beirow, B. , Giersch, T. , and Schrape, S. , 2017, “ Analysis of Mistuned Forced Response in an Axial High Pressure Compressor Rig With Focus on Tyler-Sofrin Modes,” 23rd International Conference on Air Breathing Engines, Manchester, UK, Sept. 3–8, Paper No. ISABE-2017-22614.
Crawley, E. F. , 1988, “ Aeroelasticity Formulation for Tuned and Mistuned Rotors,” AGARD Manual on Aeroelasticity in Axial-Flow Turbomachines, Vol. 2, Structural Dynamics and Aeroelasticity, M. F. Platzer and F. O. Carta, eds., AGARD Manual No. A-G 298(2). http://www.dtic.mil/dtic/tr/fulltext/u2/a199697.pdf
Newmark, N. M. , 1959, “ A Method of Computation for Structural Dynamics,” J. Eng. Mech. Div., 85(3), pp. 67–94. http://cedb.asce.org/CEDBsearch/record.jsp?dockey=0011858
Johann, E. , Mueck, B. , and Nipkau, J. , 2008, “ Experimental and Numerical Flutter Investigation of the 1st Stage Rotor in 4-Stage High Speed Compressor,” ASME Paper No. GT2008-50698.
Roeber, T. , Kuegeler, E. , and Weber, A. , 2010, “ Investigation of Unsteady Flow Effects in an Axial Compressor Based on Whole Annulus Computations,” ASME Paper No. GT2010-23522.
Schoenweitz, D. , Voges, M. , Goinis, G. , Enders, G. , and Johann, E. , 2013, “ Experimental and Numerical Examinations of a Transonic Compressor-Stage With Casing Treatment,” ASME Paper No. GT2013-95550.
Schrape, S. , Giersch, T. , Nipkau, J. , Stapelfeldt, S. , and Mück, B. , 2015, “ Tyler-Sofrin Modes in Axial High Pressure Compressor Forced Response Analyses,” 14th International Symposium on Unsteady Aerodynamics Aeroacoustics and Aeroelasticity of Turbomachines (ISUAAAT), Stockholm, Sweden, Paper No. I14-S2-3.
Beirow, B. , Kühhorn, A. , Figaschewsky, F. , Hönisch, P. , Giersch, T. , and Schrape, S. , 2017, “ Model Update and Validation of a Mistuned High Pressure Compressor Blisk,” 23rd International Conference on Air Breathing Engines, Manchester, UK, Sept. 3–8, Paper No. ISABE-2017-22568.
Hanamura, Y. , Tanaka, H. , and Yamaguchi, K. , 1980, “ A Simplified Method to Measure Unsteady Forces Acting on the Vibrating Blades in Cascade,” Bull. JSME, 23(180), pp. 880–887. [CrossRef]


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Fig. 1

Flowchart of the utilized process to generate simulated tip timing datasets

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Fig. 2

Sketch of the ith blade tip arriving at jth BTT probe at time ti,j in a section at nominal axial probe position (left) and at tip radius (right)

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Fig. 3

Geometrical sensitivity of the ith blade tip arriving at jth BTT probe at time ti,j in a section at the tip radius

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Fig. 4

Impact of sensor noise on detected TOA

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Fig. 5

Investigated blade mode family 1 (left) and calculated Campbell diagram (right)

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Fig. 6

Engine speed (top), measured envelope of SG response (middle), and converted SG response into BTT deflection (bottom) as a function of time

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Fig. 7

Sector FE-model utilized to derive the SNM

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Fig. 11

Comparison of the simulated deflection signals with the measured engine data on all blades

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Fig. 10

Comparison of ROM vibration response with the extracted amplitudes of the BTT shots A and D with and without probe fit

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Fig. 9

Comparison of the simulated deflection signals with the measured engine data on blade 11

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Fig. 8

Comparison of measured blade individual vibration amplitudes with the steady-state response of the SNM (the dots indicate a SG with high sensitivity for the mode)



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