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Research Papers: Gas Turbines: Structures and Dynamics

Identification of Asynchronous Blade Vibration Parameters by Linear Regression of Blade Tip Timing Data

[+] Author and Article Information
Abbas Rohani Bastami

Assistant Professor
Faculty of Mechanical and
Energy Engineering,
Abbaspour School of Engineering,
Shahid Beheshti University,
P.O. Box 16765-1719,
Tehran, Iran
e-mail: a_rohani@sbu.ac.ir

Pedram Safarpour

Assistant Professor
Faculty of Mechanical and
Energy Engineering,
Abbaspour School of Engineering,
Shahid Beheshti University,
P.O. Box 16765-1719,
Tehran, Iran

Arash Mikaeily, Mohammad Mohammadi

Faculty of Mechanical and
Energy Engineering,
Abbaspour School of Engineering,
Shahid Beheshti University,
P.O. Box 16765-1719,
Tehran, Iran

1Corresponding author.

Contributed by the Structures and Dynamics Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received March 29, 2017; final manuscript received December 7, 2017; published online April 16, 2018. Assoc. Editor: Philip Bonello.

J. Eng. Gas Turbines Power 140(7), 072506 (Apr 16, 2018) (8 pages) Paper No: GTP-17-1119; doi: 10.1115/1.4038880 History: Received March 29, 2017; Revised December 07, 2017

Fracture of blades is usually catastrophic and creates serious damages in the turbomachines. Blades are subjected to high centrifugal force, oscillating stresses, and high temperature which makes their life limited. Therefore, blades should be checked and replaced at specified intervals or utilize a health monitoring method for them. Crack detection by nondestructive tests can only be performed during machine overhaul which is not suitable for monitoring purposes. Blade tip timing (BTT) method as a noncontact monitoring technique is spreading for health monitoring of the turbine blades. One of the main challenges of BTT method is identification of vibration parameters from one per revolution samples which is quite below Nyquist sampling rate. In this study, a new method for derivation of blade asynchronous vibration parameters from BTT data is proposed. The proposed method requires only two BTT sensors and applies least mean square algorithm to identify frequency and amplitude of blade vibration. These parameters can be further used as blade health indicators to predict defect growth in the blades. Robustness of the proposed method against measurement noise which is an important factor has been examined by numerical simulation. An experimental test was conducted on a bladed disk to show efficiency of the proposed method.

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Copyright © 2018 by ASME
Topics: Vibration , Blades , Sensors
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References

Hohenberg, R. , 1967, “ Detection and Study of Compressor-Blade Vibration,” Exp. Mech., 7(6), pp. 19A–24A. [CrossRef]
Zablotskiy, I. Y. , and Korostelev, Y. A. , 1978, “ Measurement of Resonance Vibrations of Turbine Blades With the Elura Device,” Energomashinostroneniye, 2(2), pp. 36–39.
Zablotskiy, I. Y. , Korostelev, Y. A. , and Sviblov, L. B. , 1972, “ Contactless Measuring of Vibrations in the Rotor Blades of Turbines,” Lopatochnyye Mash. Struynyye Appar. Sb. Statey, 6, pp. 106–121.
Mix, P. E. , 2005, Introduction to Nondestructive Testing: A Training Guide, Wiley, Hoboken, NJ.
Janicki, G. , Pezouvanis, A. , Mason, B. , and Ebrahimi, M. K. , 2014, “ Turbine Blade Vibration Measurement Methods for Turbocharges,” Am. J. Sens. Technol., 2(2), pp. 13–19.
Kwapisz, D. , Hafner, M. , and Rajamani, R. , 2012, “ Application of Microwave Sensing to Blade Health Monitoring,” First European Conference of the Prognostics and Health Management Society, Dresden, Germany, Sept. 23–27.
Li, M. , Duan, F. , and Ouyan, T. , 2010, “ Analysis of Blade Vibration Frequencies From Blade Tip Timing Data,” Proc. SPIE, 7544, p. 75445F.
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]
Dimitriadis, G. , Carrington, I. B. , Wright, J. R. , and Cooper, J. E. , 2002, “ Blade-Tip Timing Measurement of Synchronous Vibrations of Rotating Bladed Assemblies,” Mech. Syst. Signal Process., 16(4), pp. 599–622. [CrossRef]
Heath, S. , and Imregun, M. , 1998, “ A Survey of Blade Tip-Timing Measurement Techniques for Turbomachinery Vibration,” ASME J. Eng. Gas Turbines Power, 120(4), pp. 784–791. [CrossRef]
Heath, S. , 1999, “A New Technique for Identifying Synchronous Resonances Using Tip-Timing,” ASME Paper No. 99-GT-402.
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]
Guru, S. S. , Shylaja, S. , Kumar, S. , and Murthy, R. , 2014, “ Pre-Emptive Rotor Blade Damage Identification by Blade Tip Timing Method,” ASME J. Eng. Gas Turbines Power, 136(7), p. 072503. [CrossRef]
Yugui, Z. , Fajie, D. , Zhiqiang, F. , Shenghua, F. , and Xiaojiang, S. , 2007, “ Frequency Identification Technique for Asynchronous Vibration of Rotating Blades,” J. Vib. Shock, 12, p. 106.
Hu, Z. , Lin, J. , Chen, Z. S. , Yang, Y. M. , and Li, X. J. , 2015, “ A Non-Uniformly Under-Sampled Blade Tip-Timing Signal Reconstruction Method for Blade Vibration Monitoring,” Sensors, 15(2), pp. 2419–2437. [CrossRef] [PubMed]
Guo, H. , Duan, F. , and Zhang, J. , 2016, “ Blade Resonance Parameter Identification Based on Tip-Timing Method Without the Once-Per Revolution Sensor,” Mech. Syst. Signal Process., 66–67, pp. 625–639. [CrossRef]
Neri, P. , 2017, “ Bladed Wheels Damage Detection Through Non-Harmonic Fourier Analysis Improved Algorithm,” Mech. Syst. Signal Process., 88, pp. 1–8. [CrossRef]
Giovanni, R. , Giuseppe, B. , and Teresa, M. B. , 2017, “ Synchronous Vibration Parameters Identification by Tip Timing Measurements,” Mech. Res. Commun., 79, pp. 7–14. [CrossRef]
Yue, L. , Liu, H. , Zang, C. , Wang, D. , Hu, W. , and Wang, L. , 2016, “ The Parameter Identification Method of Blade Asynchronous Vibration Under Sweep Speed Excitation,” J. Phys.: Conf. Ser., 744(1), p. 12051. [CrossRef]
Kharyton, V. , Dimitriadis, G. , and Defise, C. , 2017, “A Discussion on the Advancement of Blade Tip Timing Data Processing,” ASME Paper No. GT2017-63138.
Krause, C. , Giersch, T. , Stelldinger, M. , Hanschke, B. , and Kühhorn, A. , 2017, “Asynchronous Response Analysis of Non-Contact Vibration Measurements on Compressor Rotor Blades,” ASME Paper No. GT2017-63200.
Jousellin, O. , 2013, “ Blade Tip Timing Uncertainty,” U.S. Patent No. 9,494,491.
Russhard, P. , and Back, J. D. , 2014, “ Blade Tip Timing,” U.S. Patent No. 20140288865A1.
ANSI/ISA, 2013, “Industry Standard File Format for Revolution-Based Tip Timing Data,” International Society of Automation, Research Triangle Park, NC, Standard No. ANSI/ISA-107.1.
Agilis, 2018, “ Agilis Measurement Systems,” Agilis Measurement Systems Inc., Palm Beach Gardens, FL, accessed Jan. 10, 2018, www.agilismeasurementsystems.com
Prime Photonics, 2018, "Prime Photonics," Prime Photonics Inc., Blacksburg, VA, accessed Jan. 10, 2018, www.primephotonics.com
Wu, F. , Liang, L. , Xing, J. , Wang, L. , and Jia, L. , 2014, “ Blade Tip Timing Vibration Monitoring Method Based on Fiber Bragg Grating,” Photonic Sens., 4(2), pp. 188–192. [CrossRef]
Liu, C. , and Jiang, D. , 2012, “ Improved Blade Tip Timing in Blade Vibration Monitoring With Torsional Vibration of the Rotor,” J. Phys.: Conf. Ser., 364(1), p. 012136. [CrossRef]

Figures

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Fig. 1

Blade tip timing method: retarding and advancing of vibrating blade in comparison with rigid blade

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Fig. 3

Linear regression of normalized BTT parameters (Δy2=−4.061y¯2+7.3766×10−007 ), Δθ=10 deg

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Fig. 4

Linear regression of normalized BTT parameters (Δy2=−0.7679y¯2+4.4038×10−007 ), Δθ=20 deg

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Fig. 5

Error of linear regression method versus SNR in (a) estimated frequency and (b) estimated amplitude (Δθ=20 deg) 

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Fig. 2

Simulated noisy vibrational signal of blade (A=1 mm,ω=1600π rad/s,φ=π/4,  SNR=20 dB)

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Fig. 12

Arrangement of probes in the experimental tests

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Fig. 13

Diagram obtained by three parameter method by known frequency at rotational speed of 180 rpm for (a) healthy blade and (b) cracked blade

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Fig. 6

Error of linear regression method versus vibration frequency (Δθ=4 deg): (a) error of estimated frequency and (b) error of estimated amplitude

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Fig. 7

Error of linear regression method versus vibration frequency (Δθ=40 deg): (a) estimated frequency and (b) estimated amplitude

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Fig. 8

Experimental setup

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Fig. 9

Blade vibration caused by an unbalance vibrator (rotor is not rotating)

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Fig. 11

Experimental test rig: (a) sensor arrangement to eliminate the effect of torsional vibrations, (b) cracked blade with the attached vibrator, and (c) blade root marker aligned in the direction of the blade

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Fig. 14

Linear regression of normalized BTT parameters at rotational speed of 180 rpm

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Fig. 10

(a) Encoder connected to the shaft to record torsional vibrations and (b) instantaneous rotational speed of the rotor at average speed of 180 rpm

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