Abstract
Detection of cracks in shafts plays a critical role in maintenance. A crack can cause a catastrophic failure with costly processes of reparation. The aim of condition monitoring and fault diagnostics is to detect and to distinguish different kinds of faults. In this work vibration signals are obtained from an analytical Jeffcott rotor model and a real rotating machine during working. The aim was to identify indicators of the presence of a crack, to allow the inverse process of detecting a crack and its size for the machine tested. Signals were processed using the Wavelet Packets Transform. In signals obtained from the analytical model, the best indicators of crack were frequencies related to the first’s harmonics of the rotation speed. However, when matching the theoretical results with the experimental ones, only harmonics higher than the 2× component of the rotation speed seemed to feel that changes in practice.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Papadopoulos C (2008) The strain energy release approach for modeling cracks in rotors: a state of the art review. Mech Syst Signal Process 22:763–789
Sabnavis G, Kirk R, Kasarda M, Quinn D (2004) Cracked shaft detection and diagnostics: a literature review. Shock Vib Digest 36:287–296
Gomez-Mancilla J, Sinou J, Nosov V (2004) The influence of crack-imbalance orientation and orbital evolution for an extended cracked jeffcott rotor. CR Mec 332(12):962–995
Bachschmid N, Penacci P (2008) Editorial. Crack effects in rotordynamics. Mech Syst Signal Process 22:761–762
Sekhar A (2004) On-line rotor fault identification by combined model and signal based approach. Noise Vib Worldw 35(7):16–30
Mallat S (1998) A wavelet tour of signal processing. Academic Press, San Diego
Peng Z (2004) Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography. Mech Syst Signal Process 18:199–221
Lou X, Loparo K (2004) Bearing fault diagnosis based on wavelet transform and fuzzy inference. Mech Syst Signal Process 18(5):1077–1095
Bin G, Gao J, Li X, Dhillon B (2012) Early fault diagnosis of rotating machinery based on wavelet packets-empirical mode decomposition feature extraction and neural network. Mech Syst Signal Process 27:696–711
Hu Q, He Z, Zhang Z, Zi Y (2007) Fault diagnosis of rotating machinery based on improved wavelet package transform and svms ensemble. Mech Syst Signal Process 21:688–705
Feng Y, Schlindwein F (2009) Normalized wavelet packets quantifiers for condition monitoring. Mech Syst Signal Process 23:712–723
Stoisser C, Audebert S (2012) A comprehensive theoretical, numerical and experimental approach for crack detection in power plant rotating machinery. Mech Syst Signal Process 22:818–844
Machorro J (2005) Doctoral thesis, Nacional Politecnic Institute, México
Al-Shudeifat M, Butcher E (2011) New breathing functions for the transverse breathing crack of the cracked rotor system: approach for critical and subcritical harmonic analysis. J Sound Vib 330:526–544
Gash R (1976) Dynamic behavior of a simple rotor with a cross-sectional crack
Mayes I, Davies W (1984) Analysis of the response of a multi-rotor bearing system containing a transverse crack in a rotor. J Vib Acoust Stress Reliab Design Trans ASME 106:139–145
Illescas RG (2005) Static and Dynamic Analysis of cracked rotors and its structural behavior Doctoral thesis, SEPI-ESIME, IPN
Castejón C, García-Prada J, Gómez M, Meneses J (2014) Automatic detection of cracked rotors combining multiresolution analysis and artificial neural networks. J Vib Control. doi:10.1177/1077546313518816
Gómez M, Castejón C, García-Prada J (2014) Incipient fault detection in bearings through the use of WPT energy and neural networks. Advances in condition monitoring of machinery in non-stationary operations. Lecture Notes in Mechanical Engineering, Springer, pp 63-72
Acknowledgments
The authors are grateful for funding under the project CDTI-Rankine21 2010/00615.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Gómez, M.J., Castejón, C., García-Prada, J.C., López, J. (2015). Experimental Analysis and Validation of a Vibration-Based Technique for Crack Detection in a Shaft. In: Pennacchi, P. (eds) Proceedings of the 9th IFToMM International Conference on Rotor Dynamics. Mechanisms and Machine Science, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-319-06590-8_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-06590-8_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06589-2
Online ISBN: 978-3-319-06590-8
eBook Packages: EngineeringEngineering (R0)