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Shaft-stator rub and cracks on rotors, which have devastating effects on the industrial equipment, cause non-linear and in some cases chaotic lateral vibrations. On the other hand, vibrations caused by machinery fault scan be torsional in cases such as rub. Therefore, a combined analysis of lateral and torsional vibrations and extraction of chaotic features from these vibrations is an effective approach for rotor vibration monitoring. In this study, lateral and torsional vibrations of rotors have been examined for detecting cracks and rub. For this purpose, by preparing a laboratory model, the lateral vibrations of a system with crack and rub have been acquired. After that, a practical method for measuring the torsional vibrations of the system is introduced. By designing and installing this measurement system, practical test data were acquired on the laboratory setup. Then, the method of phase space reconstruction was used to examine the effect of faults on the chaotic behaviour of the system. In order to diagnose the faults based on the chaotic behaviour of the system, largest Lyapunov exponent (LLE), approximate entropy (ApEn) and correlation dimension were calculated for a healthy system and also for a system with rub and a crack. Finally, by applying these parameters, the chaotic feature space is introduced in order to diagnose the intentionally created faults. The results show that in this space, the distinction between the various defects in the system can be clearly identified, which enables to use this method in fault diagnosis of rotating machinery.
Czasopismo
Rocznik
Tom
Strony
65--80
Opis fizyczny
Bibliogr. 26 poz., rys., wykr., wzory
Twórcy
autor
- Shahid Chamran University of Ahvaz, Faculty of Engineering, Ahvaz, Daneshgah Square, Iran
autor
- Shahid Chamran University of Ahvaz, Faculty of Engineering, Ahvaz, Daneshgah Square, Iran
autor
- Shahid Chamran University of Ahvaz, Faculty of Engineering, Ahvaz, Daneshgah Square, Iran
Bibliografia
- [1] Abadi, M.K.B., Hajnayeb, A., Hosseingholizadeh, A., Ghasemloonia, A. (2011). Single and multiple misfire detection in internal combustion engines using vold-kalman filter order-tracking. SAE Technical Paper.
- [2] Qin, Y. (2018). A new family of model-based impulsive wavelets and their sparse representation for rolling bearing fault diagnosis. IEEE Transactions on Industrial Electronics, 65, 2716-26.
- [3] Zak, G., Wylomanska, A., Zimroz, R. (2018). Local damage detection method based on distribution distances applied to time-frequency map of vibration signal. IEEE Transactions on Industry Applications.
- [4] Azizi, R., Attaran, B., Hajnayeb, A., Ghanbarzadeh, A. Changizian, M. (2017). Improving accuracy of cavitation severity detection in centrifugal pumps using a hybrid feature selection technique. Measurement, 108, 9-17.
- [5] Deng, W., Yao, R., Zhao, H., Yang, X., Li, G. (2017). A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm. Soft Computing, 1-18.
- [6] Hajnayeb, A., Ghasemloonia, A., Khadem, S., Moradi, M. (2011). Application and comparison of an ANN-based feature selection method and the genetic algorithm in gearbox fault diagnosis. Expert Systems with Applications, 38, 10205-10209.
- [7] Jiang, Y., Zhu, H., Li, Z. (2016). A new compound faults detection method for rolling bearings based on empirical wavelet transform and chaotic oscillator. Chaos, Solitons & Fractals, 89, 8-19.
- [8] Li, Z., Peng, Z. (2016). A new nonlinear blind source separation method with chaos indicators for decoupling diagnosis of hybrid failures: A marine propulsion gearbox case with a large speed variation. Chaos, Solitons & Fractals, 89, 27-39.
- [9] Medina, R., Alvarez, X., Jadán, D., Cerrada, M., Sánchez, R.V., Macancela, J.C. (2017). Poincaré plot features from vibration signal for gearbox fault diagnosis. Ecuador Technical Chapters Meeting (ETCM), 1-6.
- [10] Wang, W., Chen, J., Wu, Z. (2000). The application of a correlation dimension in large rotating machinery fault diagnosis. Proc. of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 921-930.
- [11] Wang, W., Wu, Z., Chen, J. (2001). Fault identification in rotating machinery using the correlation dimension and bispectra. Nonlinear Dynamics, 25, 383-393.
- [12] Zhihong, Z., Yongqiang, L. (2012). Wheelset bearing vibration analysis based on nonlinear dynamical method. Journal of Theoretical & Applied Information Technology, 45.
- [13] Shuting, W., Heming, L., Zhaofeng, X. (2002). A new method of turbine-generator vibration fault diagnosis based on correlation dimension and ANN. Power System Technology, Proc. PowerCon 2002 International Conference, 1655-1659.
- [14] Yan, R., Gao, R.X. (2007). Approximate entropy as a diagnostic tool for machine health monitoring. Mechanical Systems and Signal Processing, 21, 824-839.
- [15] He, Y., Zhang, X. (2012). Approximate entropy analysis of the acoustic emission from defects in rolling element bearings. Journal of Vibration and Acoustics, 134, 061012.
- [16] Zhou, B., Lu, C., Li, L., Chen, Z. (2016). Health assessment for rolling bearing based on local characteristic-scale decomposition - Approximate entropy and manifold distance. Intelligent Control and Automation (WCICA), 401-406.
- [17] Sadooghi, M.S., Khadem, S.E. (2018). Improving one class support vector machine novelty detection scheme using nonlinear features. Pattern Recognition, 83, 14-33.
- [18] Wang, L, Wang, H, Zhang, K, Zhao, W. (2007). Application of Lyapunov exponents to fault diagnosis of rolling bearing. Noise and Vibration Control, 5, 104-105.
- [19] Lu, C., Sun, Q., Tao, L., Liu, H., Lu, C. (2013). Bearing health assessment based on chaotic characteristics. Shock and Vibration, 20, 519-530.
- [20] Soleimani, A., Khadem, S. (2015). Early fault detection of rotating machinery through chaotic vibration feature extraction of experimental data sets. Chaos, Solitons & Fractals, 78, 61-75.
- [21] Vance, J., French, R. (1986). Measurement of torsional vibration in rotating machinery. Journal of Mechanisms, Transmissions, and Automation in Design, 108, 565-577.
- [22] Maynard, K.P., Trethewey, M. (1999). On the feasibility of blade crack detection through torsional vibration measurements. Proce. of the 53 rd Meeting of the Society for Machinery Failure Prevention Technology, Virginia Beach, 451-459.
- [23] Resor, B.R., Trethewey, M.W., Maynard, K.P. (2005). Compensation for encoder geometry and shaft speed variation in time interval torsional vibration measurement. Journal of Sound and Vibration, 286, 897-920.
- [24] Trethewey, M.W., Lebold, M.S., Turner, M.W. (2011). Minimally intrusive torsional vibration sensing on rotating shafts. Structural Dynamics, 3, 207-212.
- [25] Rosenstein, M.T., Collins, J.J., De Luca, C.J. (1993). A practical method for calculating largest Lyapunov exponents from small data sets. Physica D: Nonlinear Phenomena, 65, 117-134.
- [26] Grassberger, P., Procaccia, I. (1983). Measuring the strangeness of strange attractors. Physica D: Nonlinear Phenomena, 9, 189-208.
Uwagi
EN
1. The authors would like to thank Shahid Chamran University of Ahvaz for their financial support.
PL
2. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-40c83040-dcf4-492a-a8ac-480ac2b68890