A Review of Vibration Monitoring as a Diagnostic Tool for Turbine Blade Faults

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Vibration monitoring is widely recognized as an effective tool for the detection and diagnosis of incipient failures of gas turbines. This paper presents a review of vibration based methods for turbine blade faults. Methods typically involved analysis of blade passing frequencies, and extraction of dynamic signals from the measured vibration response. This includes frequency analysis, wavelet analysis, neural networks and fuzzy logic and model based analysis. The literature reviewed showed that vibration could detect most types of blade faults on the basis that dynamic signals are correctly extracted using the most appropriate signal processing method.

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Edited by:

Mohamed Othman

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1459-1463

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A. M. Abdelrhman et al., "A Review of Vibration Monitoring as a Diagnostic Tool for Turbine Blade Faults", Applied Mechanics and Materials, Vols. 229-231, pp. 1459-1463, 2012

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November 2012

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[1] N. Goel, a Kumar, V. Narasimhan, a Nayak, and a Srivastava: Health risk assessment and prognosis of gas turbine blades by simulation and statistical methods. Canadian Conference on Electrical and Computer Engineering, Niagara Falls. May 2008, pp.001087-001092.

DOI: https://doi.org/10.1109/ccece.2008.4564705

[2] Meher-Homji, C.B. (1995b). Blading Vibration and Failures in Gas Turbines: Part B, Compressor and Turbine Airfoil Distress. ASME paper no. 95-GT-419.

DOI: https://doi.org/10.1115/95-gt-419

[3] M Salman LEONG: Field Experiences of Gas Turbines Vibrations -A Review and Case Studies. Journal of System Design and Dynamics. Vol. 2, No. 1 (2008), pp.24-35.

DOI: https://doi.org/10.1299/jsdd.2.24

[4] Simmons, H.R. (1986). A Non-Intrusive Method for Detecting HP Blade Resonance. ASME Paper No. 86-JPGC-Pwr-36.

[5] Simmons, H.R. (1987). Non-Intrusive Detection of Turbine Blade Resonance. Third EPRI Conference on Incipient Failure Detection in Power Plants, Philadelphia, March 10–12, (1987).

[6] Parge, P., Trevillion, B., Carle, P: Machinery Interactive Display and Analysis System Description and Applications. Proceedings of the First International Machinery Monitoring and Diagnostic Conference. Las Vegas, Nevada . Sept 11-14, 1989. Pp. 176-182.

[7] Parge, P: Non-Intrusive Vibration Monitoring for Turbine Blade Reliability. Proceedings of Second International Machinery Monitoring and Diagnostic Conference. Los Angeles, California. , Oct 22-25, 1990. Pp. 435- 446.

[8] R. Beebe: Condition monitoring of steam turbines by performance analysis. Journal of Quality in Maintenance Engineering. Vol. 9. 2003. No2.

[9] K.N. GUPTA: Vibration - A tool for machine diagnostics and condition monitoring, " Sadhana, vol. Vol. 22, 1997, pp.393-410.

DOI: https://doi.org/10.1007/bf02744480

[10] Tumer, I. Y., and Bajwa, A: A survey of aircraft engine health monitoring systems. 35th AIAA/ASME/SAE/ASEE Joint Propulsion Conf. and Exhibit. Los Angeles, USA, 1999 . pp -99-2528.

DOI: https://doi.org/10.2514/6.1999-2528

[11] Kuo, R. J. Intelligent Diagnosis for Turbine Blade Faults Using Artificial Neural Network & Fuzzy Logic. Engineering Application of Artificial Intelligence, Vol. 8. (1995). Pp. 25-34.

DOI: https://doi.org/10.1016/0952-1976(94)00082-x

[12] U. Südmersen, O. Pietsch, C. Scheer, W. Reimche, and Reimche: Condition Monitoring Of Steam Turbines By Combined Vibration And Process Parameter Analysis. 6th COTEQ, Conference, Salvador BA, Brazil: (2002).

DOI: https://doi.org/10.1016/b978-008044036-1/50020-2

[13] Jorge Moreno Barragán, Engine Vibration Monitoring and Diagnosis Based on On-Board Captured Data, RTO AVT Symposium, Manchester, UK: RTO-MP-079(I), 2001, pp.8-11.

[14] F. Cong, J. Chen, G. Dong, and K. Huang, Experimental validation of impact energy model for the rub–impact assessment in a rotor system, Mechanical Systems and Signal Processing, 2011, pp.1-10.

DOI: https://doi.org/10.1016/j.ymssp.2011.04.004

[15] P. Vaněk, František; Procházka, Contactless Diagnostics of Turbine Blade Vibration and Damage Pavel, Journal of Physics, vol. 305, 2011, pp. pp.12116-12126(11).

DOI: https://doi.org/10.1088/1742-6596/305/1/012116

[16] Maynard, K. P., and Trethewey, M. W., Blade and Shaft Crack detection Using Torsional Vibration Measurements Part 1: Feasibility Studies, Noise and Vibration worldwide, Volume 31, No. 11, December 2000, pp.9-15.

DOI: https://doi.org/10.1260/0957456001498723

[17] Maynard, K. P., and Trethewey, M. W., Blade and Shaft Crack detection Using Torsional Vibration Measurements Part 2: Resampling to Improve Effective Dynamic Range, Noise and Vibration worldwide, Volume 32, No. 2, February 2001, pp.23-26.

DOI: https://doi.org/10.1260/0957456011498281

[18] Maynard, K.P. and Trethewey, M. W, Blade and Shaft Crack Detection using Torsional Vibration Measurements. Part 3: Field Application Demonstrations, Noise and Vibration Worldwide, Vol. 32, No. 12, pp.16-23., (2001).

DOI: https://doi.org/10.1260/0957456011499145

[19] T. KAWASIklA, H. I. and N. bIINAGAW., & Industries, I. -harirna H. Optical Semiconductor Blade Vibration Monitoring System for Gas Turbine Engine. IEEE 601, 2(10-12 May 1994). p.601 – 604.

[20] N. Aretakis and K. Mathioudakis. Wavelet Analysis for Gas Turbine Fault Diagnostics. Journal of Engineering for Gas Turbines and Power. vol. 119, 1997, p.870.

DOI: https://doi.org/10.1115/1.2817067

[21] Aretakis, N., Mathioudakis, K. Wavelet Analysis for Gas Turbine Fault Diagnostics., ASME Journal of Engineering for Gas Turbine and Power. Vol. 119. (1997). Pp. 870-876.

DOI: https://doi.org/10.1115/1.2817067

[22] Yuan, Q., Xie, H., Meng, Q. J Fault Diagnosis of Turbine Blade by Wavelet., A-PVC Conference. Nanyang Technological University Singapore. Vol. 1. 1999. Pp. 170-175.

[23] L.M. Hee M. salman leong, Improved Blade Fault Diagnosis Using Discrete Blade Passing Energy Packet and Rotor Dynamics Wavelet Analysis, ASME Turbo Expo . Glasgow, UK. June, 2010, pp.1-7. 19.

DOI: https://doi.org/10.1115/gt2010-22218

[24] M.H. Lim and M.S. Leong, Diagnosis for Loose Blades in Gas Turbines Using Wavelet Analysis, Journal of Engineering for Gas Turbines and Power, vol. 127, 2005, p.314.

DOI: https://doi.org/10.1115/1.1772406

[25] C. Chang, Damage detection of cracked thick rotating blades by a spatial wavelet based approach, Applied Acoustics, vol. 65, Nov. 2004, pp.1095-1111. `.

DOI: https://doi.org/10.1016/j.apacoust.2004.03.006

[26] James Turso, Charles Lawrence, and Jonathan Litt. Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreig Object Damage (FOD) Events., NASA TM-2004-213118 ARLTR- 3256.

DOI: https://doi.org/10.1115/1.2718230

[27] F. Al-badour, M. Sunar, and L. Cheded, Vibration analysis of rotating machinery using time – frequency analysis and wavelet techniques, Mechanical Systems and Signal Processing, vol. 25, no. 6, 2011. pp. (2083).

DOI: https://doi.org/10.1016/j.ymssp.2011.01.017

[28] A. Kyriazis, N. Aretakis, and K. Mathioudakis, Gas Turbine Fault Diagnosis From Fast Response Data Using Probabilistic Methods & Information Fusion, in proceedings of GT2006 ASME Turbo Expo: Power for Land, Sea & Air, Barcelona, Spain, May 8–11, 2006 pp.1-9.

DOI: https://doi.org/10.1115/gt2006-90362

[39] Angelakis, C., Loukis, E.N., Pouliezos, A. D, Starvrakakis, G.S. A Neural Network-Based Method for Gas Turbine Blading Fault Diagnosis., International Journal of Modelling and Simulation. Vol. 21. (2001). Pp. 51-60.

[30] Loukis, E., Mathioudakis, K., Papailiou, K. A Procedure for Automated Gas Turbine Blade Faults Identification Based on Spectral Pattern Analysis., ASME Journal of Engineering for Gas Turbine and Power, Vol. 114. (1992). Pp. 201-208.

DOI: https://doi.org/10.1115/1.2906573

[31] G Y Ying, X Z Tong, S L Liu in Dongli Gongcheng Xuebao, Journal of Chinese Society of Power Engineering (2011).

[32] Satyam, M., Rao, Devy, CG. Ceptrum Analysis an Advanced Technique in Vibration Analysis of Defects in Rotating Machinery., Defence Science Journal, Vol. 44. 1994. Pp. 53-60.

DOI: https://doi.org/10.14429/dsj.44.4151

[33] Kubiak, J. A, Franco, J.M., Carnero, A., Rothhirsch, A., Aguirre, L.J. Diagnosis of Failure of a Compressor Blade., ASME (paper), Paper Presented at the ASME Gas Turbine Conference and Exhibition. 1987. Paper no. 87-GT-45.