Diagnosis and condition monitoring in rotating machinery has been a subject of intense research for the last century. Recent developments indicate the drive towards integration of diagnosis and prognosis algorithms in future integrated vehicle health management (IVHM) systems. With this in mind, this paper concentrates on highlighting some of the latest research on common faults in rotating machines. Eight key faults have been described; the selected faults include unbalance, misalignment, rub/looseness, fluid-induced instability, bearing failure, shaft cracks, blade cracks, and shaft bow. Each of these faults has been detailed with regard to sensors, fault identification techniques, localization, prognosis, and modeling. The intent of the paper is to highlight the latest technologies pioneering the drive towards next-generation IVHM systems for rotating machinery. 1. Introduction The topic of diagnosing and prognosing faults in rotating machinery is an ongoing subject of research, with many developments published in a range of conferences and journals annually. This research has the potential to become even more relevant in the coming years due to the rise of IVHM, in which the drive towards condition-based maintenance and whole vehicle monitoring plays a vital role. This paper intends to survey some of the recent developments in the field, with the aim of summarizing some of the more promising studies and trends with relevance to future IVHM systems for rotating machinery. Modern day rotating machines operate with a high level of reliability, and yet the drive for ever increased operation and decreased unscheduled maintenance is providing additional challenges for industry. The airline industry provides a current example of this desire, with airlines pushing manufacturers to enable shorter turnaround times and to keep aircraft in the air longer, increasing cost benefit. Despite the high level of reliability, the rotordynamic faults detailed in this paper remain aspects which require consideration in this drive for increased reliability and improved maintenance procedures [1]. In order to fully understand and summarize the trends and developments in this area, several hundred recent conference and journal papers have been studied. Overall trends have been highlighted and discussed alongside specific papers of relevance. It is intended that the work should provide a broad reference and summary for working engineers on some of the latest developments in rotordynamic fault diagnosis and prognosis, with specific application to papers of industrial
References
[1]
I. K. Jennions, Integrated Vehicle Health Management: Perspectives on an Emerging Field, 2011.
[2]
G. Anderson, “Providing best-value IVHM solutions for aging aircraft,” in Proceedings of the 9th Joint FAA/DoD/NASA Aging Aircraft Conference, vol. 1, pp. 1–11, 2005.
[3]
A. Muszynska, Rotordynamics, Taylor & Francis, 1st ed edition, 2005.
[4]
D. E. Bently, Fundimentals of Rotating Machinery Diagnostics, ASME Press, 1st edition, 2002.
[5]
B. Domes, “Vibration phenomena in aero-engines,” in Proceedings of the 9th International Conference on Vibrations in Rotating Machinery Exeter (IMechE '08), vol. 1, pp. 15–32, September 2008.
[6]
A. Hess, G. Calvello, and T. Dabney, “PHM a key enabler for the JSF autonomie logistics support concept,” in Proceedings of the IEEE Aerospace Conference Proceedings, pp. 3543–4549, March 2004.
[7]
S. N. Ganeriwala, B. Schwarz, and M. H. Richardson, “Operating deflection shapes detect unbalance in rotating equipment,” Sound and Vibration, vol. 43, no. 5, pp. 11–13, 2009.
[8]
G. N. D. S. Sudhakar and A. S. Sekhar, “Identification of unbalance in a rotor bearing system,” Journal of Sound and Vibration, vol. 330, no. 10, pp. 2299–2313, 2011.
[9]
T. Yang and M. W. Hsu, “An efficient diagnosis technique for variations of shaft-bow and unbalance,” in Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (DETC '09), pp. 57–66, San Diego, Calif, USA, September 2009.
[10]
A. El-Shafei, S. H. Tawfick, and M. O. A. Mokhtar, “Experimental investigation of the effect of angular misalignemt on the instability of plain journal bearings,” in Proceedings of the ASME/STLE International Joint Tribology Conference (IJTC '09), pp. 171–173, Memphis, Tenn, USA, October 2009.
[11]
A. El-Shafei, S. H. Tawfick, and M. O. A. Mokhtar, “Misalignment modeling in rotating systems,” in Proceedings of the ASME Turbo Expo, H. Bahaloo, A. Ebrahimi, and M. Samadi, Eds., vol. 1711, pp. 973–979, Orlando, Fla, USA, June 2009.
[12]
L. F. Villa, et al., “Statistical diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load,” Mechanical Systems and Signal Processing, vol. 29, pp. 436–446, 2012.
[13]
C. F. Ngolah, et al., “Intelligent fault recognition and diagnosis for rotating machines using neural networks,” Software Science and Computational Intelligence, vol. 3, no. 4, 17 pages, 2011.
[14]
Y. Lu, Z. Ren, H. Chen, N. Song, and B. Wen, “Study on looseness and impact—rub coupling faults of a vertical dual-disk cantilever rotor- Bearing system,” Key Engineering Materials, vol. 353–358, no. 4, pp. 2479–2482, 2007.
[15]
Q. Han, Z. Zhang, and B. Wen, “Periodic motions of a dual-disc rotor system with rub-impact at fixed limiter,” Proceedings of the Institution of Mechanical Engineers, vol. 222, no. 10, pp. 1935–1946, 2008.
[16]
H. F. de Castro, K. L. Cavalca, and R. Nordmann, “Whirl and whip instabilities in rotor-bearing system considering a nonlinear force model,” Journal of Sound and Vibration, vol. 317, no. 1-2, pp. 273–293, 2008.
[17]
C. C. Fan, et al., “Mechanical systems and signal processing,” Study of Start-Up Vibration Response for Oil Whirl and Dry Whip, vol. 25, pp. 3102–3115, 2011.
[18]
K. Kappaganthu and C. Nataraj, “Nonlinear modeling and analysis of a rolling element bearing with a clearance,” Communications in Nonlinear Science and Numerical Simulation, vol. 16, no. 10, pp. 4134–4145, 2011.
[19]
T. C. Gupta, K. Gupta, and D. K. Sehgal, “Instability and chaos of a flexible rotor ball bearing system: an investigation on the influence of rotating imbalance and bearing clearance,” Journal of Engineering for Gas Turbines and Power, vol. 133, no. 8, Article ID 082501, 11 pages, 2011.
[20]
J. Hong, X. Miao, L. Han, and Y. Ma, “Prognostics model for predicting aero-engine bearing grade-life,” in Proceedings of the ASME Turbo Expo, vol. 1, pp. 639–647, Orlando, Fla, USA, June 2009.
[21]
P. Borghesani, P. Pennacchi, R. B. Randall, N. Sawalhi, and R. Ricci, “Application of cepstrum pre-whitening for the diagnosis of bearing faults under variable speed conditions,” Mechanical Systems and Signal Processing, 2012.
[22]
Y. Li, J. Zhang, L. Dai, Z. Zhang, and J. Liu, “Auditory-model-based feature extraction method for mechanical faults diagnosis,” Chinese Journal of Mechanical Engineering (English Edition), vol. 23, no. 3, pp. 391–397, 2010.
[23]
N. Bachschmid, P. Pennacchi, and E. Tanzi, “Cracked rotating shafts: typical behaviors, modeling and diagnosis,” IUTAM Symposium on Emerging Trends in Rotor Dynamics, vol. 1011, pp. 441–454, 2011.
[24]
T. Inoue, N. Nagata, and Y. Ishida, “Fem modelling and experimental verification of a rotor system with a open crack,” in Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (DETC '09), pp. 1113–1122, San Diego, Calif, USA, September 2009.
[25]
H. E. Sonnichsen, “Real-time detection of developing cracks in jet engine rotors,” in Proceedings of the IEEE Aerospace Conference, pp. 173–184, March 2000.
[26]
I. Green and C. Casey, “Crack detection in a rotor dynamic system by vibration monitoring—part I: analysis,” Journal of Engineering for Gas Turbines and Power, vol. 127, no. 2, pp. 425–436, 2005.
[27]
J. T. Sawicki, M. I. Friswell, A. H. Pesch, and A. Wroblewski, “Condition monitoring of rotor using active magnetic actuator,” in Proceedings of the ASME Turbo Expo, pp. 1257–1265, Berlin, Germany, June 2008.
[28]
J. Xiang, X. Chen, Q. Mo, and Z. He, “Identification of crack in a rotor system based on wavelet finite element method,” Finite Elements in Analysis and Design, vol. 43, no. 14, pp. 1068–1081, 2007.
[29]
M. G. Maalouf, “Slow speed vibration signal analysis: if you can't do it slow, you can't do it fast,” in Proceedings of the ASME Turbo Expo, pp. 559–567, Montreal, Canada, May 2007.
[30]
J. Meagher, X. Wu, and C. Lencioni, “Response of a warped flexible rotor with a fluid bearing,” International Journal of Rotating Machinery, vol. 2008, Article ID 147653, 9 pages, 2008.
[31]
T. Gaka and M. Tabaszewski, “An application of statistical symptoms in machine condition diagnostics,” Mechanical Systems and Signal Processing, vol. 25, no. 1, pp. 253–265, 2011.
[32]
J. K. Sinha, “Recent trands in fault quantification in rotating machines,” Advances in Vibration EngIneerIng, vol. 8, no. 1, pp. 79–85, 2009.
[33]
X. Shen, J. Jia, and M. Zhao, “Nonlinear analysis of a rub-impact rotor-bearing system with initial permanent rotor bow,” Archive of Applied Mechanics, vol. 78, no. 3, pp. 225–240, 2008.
[34]
A. W. Lees, J. K. Sinha, and M. I. Friswell, “Model-based identification of rotating machines,” Mechanical Systems and Signal Processing, vol. 23, no. 6, pp. 1884–1893, 2009.
[35]
L. C. Jaw and W. Merrill, “CBM+ research environment—facilitating technology development, experimentation, and maturation,” in Proceedings of the IEEE Aerospace Conference (AC '08), March 2008.
[36]
R. Walker, S. Perinpanayagam, and I. K. Jennions, “Simulating Unbalance for Future IVHM Applications,” in Proceedings of the Society for Experimental Mechanics (IMAC '12), vol. 29, pp. 141–148, May 2012.
[37]
H. C. Pusey, “Turbomachinery condition monitoring and failure prognosis,” Sound and Vibration, vol. 41, no. 3, pp. 10–15, 2007.
[38]
J. R. Jain and T. K. Kundra, “Model based online diagnosis of unbalance and transverse fatigue crack in rotor systems,” Mechanics Research Communications, vol. 31, no. 5, pp. 557–568, 2004.
[39]
K. R. Wheeler, T. Kurtoglu, and S. D. Poll, “A survey of health management user objectives related to diagnostic and prognostic metrics,” in Proceedings of the 29th Computers and Information Engineering Conference, vol. 2, pp. 1287–1298, 2009.
[40]
G. Vachtsevanos, “Performance metrics for fault prognosis of complex systems,” in IEEE Systems Readiness Technology Conference (AUTOTESTCON '03), pp. 341–345, September 2003.
[41]
A. Saxena, J. Celaya, E. Balaban et al., “Metrics for evaluating performance of prognostic techniques,” in Proceedings of the International Conference on Prognostics and Health Management (PHM '08), pp. 1–17, October 2008.
