Envelope Analysis on Vibration Signals for Stator Winding Fault Early Detection in 3-Phase Induction Motors
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Published
Nov 1, 2020
Chao Jin
Agusmian P. Ompusunggu
Zongchang Liu
Hossein D. Ardakani
Fredrik Petré
Jay Lee
Abstract
This paper brings up a novel method for detecting induction motor stator winding faults at an early stage. The contribution of the work comes from the delicate handling of motor
vibration by applying envelope analysis, which makes it possible to capture electrical short-circuit signature in mechanical signals, even if the magnitude of the fault is fairly incipient. Conventional induction motor condition-based maintenance methods usually involve current and voltage measurements, which could be expensive to collect, and vibration-based analysis is often only capable of detecting the fault when it is already quite significant. In contrast, the solution presented in this study provides a refreshing perspective by applying time synchronous averaging to remove the discrete frequency component, and amplitude demodulation to further enhance the signal with the help of kurtogram. Experimental results on a three-phase induction motor show that the method is also able to distinguish different fault severity levels.
##plugins.themes.bootstrap3.article.details##
Keywords
vibration monitoring, early fault detection, Envelope Analysis, Induction Motor
References
Al-Atat, H., Siegel, D. & Lee, J. (2011). A systematic methodology for gearbox health assessment and fault classification. Int J Prognostics Health Manage Soc, vol. 2(1), pp. 16.
Antoni, J. (2007). Fast computation of the kurtogram for the detection of transient faults. Mechanical Systems and Signal Processing, vol. 21(1), pp. 108-124.
Antoni, J. & Randall, R. (2006). The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mechanical Systems and Signal Processing, vol. 20(2), pp. 308-331.
Bechhoefer, E. & Kingsley, M. (2009). A review of time synchronous average algorithms. Annual conference of the prognostics and health management society
Bell, R., McWilliams, D., O'Donnell, P., Singh, C. & Wells, S. (1985). Report of large motor reliability survey of industrial and commercial installations. I. IEEE Transactions on Industry Applications, vol. 21(4), pp. 853-864.
Cardoso, A. M., Cruz, S. & Fonseca, D. (1999). Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park's vector approach. Energy Conversion, IEEE Transactions on, vol. 14(3), pp. 595-598.
Djurović, S., Vilchis-Rodriguez, D. S. & Smith, A. C. (2014) Investigation of wound rotor induction machine vibration signal under stator electrical fault conditions. The Journal of Engineering.
Eftekhari, M., Moallem, M., Sadri, S. & Hsieh, M.-F. (2013). Online Detection of Induction Motor's Stator Winding Short-Circuit Faults. Systems Journal, IEEE, vol. 8(4), pp. 1272 - 1282. doi: 10.1109/JSYST.2013.2288172
Furfari, F. & Brittain, J. (2002). Charles LeGeyt Fortescue and the method of symmetrical components. Industry Applications Magazine, IEEE, vol. 8(3), pp. 7-9.
Jablonski, A. & Barszcz, T. (2013). Validation of vibration measurements for heavy duty machinery diagnostics. Mechanical Systems and Signal Processing, vol. 38(1), pp. 248-263.
Jabłoński, A., Barszcz, T. & Bielecka, M. (2011). Automatic validation of vibration signals in wind farm distributed monitoring systems. Measurement, vol. 44(10), pp. 1954-1967.
Jardine, A. K., Lin, D. & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, vol. 20(7), pp. 1483-1510.
Jover Rodríguez, P. V. & Arkkio, A. (2008). Detection of stator winding fault in induction motor using fuzzy logic. Applied Soft Computing, vol. 8(2), pp. 1112-1120.
Kliman, G., Premerlani, W., Koegl, R. & Hoeweler, D. (1996). A new approach to on-line turn fault detection in AC motors. Industry Applications Conference, 1996. Thirty-First IAS Annual Meeting, IAS'96., Conference Record of the 1996 IEEE (687-693)
Kliman, G. & Stein, J. (1992). Methods of motor current signature analysis. Electric Machines and power systems, vol. 20(5), pp. 463-474.
Kohler, J. L., Sottile, J. & Trutt, F. C. (2002). Condition monitoring of stator windings in induction motors. I. Experimental investigation of the effective negative-sequence impedance detector. Industry Applications, IEEE Transactions on, vol. 38(5), pp. 1447-1453.
Lamim Filho, P., Pederiva, R. & Brito, J. (2014). Detection of stator winding faults in induction machines using flux and vibration analysis. Mechanical Systems and Signal Processing, vol. 42(1), pp. 377-387.
Lamim, P., Brito, J. N., Silva, V. A. D. & Pederiva, R. (2013). Detection of Electrical Faults in Induction Motors Using Vibration Analysis. Journal of Quality in Maintenance Engineering, vol. 19(4), pp. 2-2.
Lin, J. & Qu, L. (2000). Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis. Journal of sound and vibration, vol. 234(1), pp. 135-148.
Nandi, S., Toliyat, H. A. & Li, X. (2005). Condition monitoring and fault diagnosis of electrical motors-a review. Energy Conversion, IEEE Transactions on, vol. 20(4), pp. 719-729.
Ompusunggu, A. P., Liu, Z., Ardakani, H. D., Jin, C., Petre, F. & Lee, J. (2014). Winding fault diagnosis of a 3-phase induction motor powered by frequency-inverter drive using the current and voltage signals. Proceedings of the 14th Mechatronics Forum International Conference. June 16-18, Karlstad (Sweden)
Randall, R. B. & Antoni, J. (2011). Rolling element bearing diagnostics—a tutorial. Mechanical Systems and Signal Processing, vol. 25(2), pp. 485-520.
Randall, R. B. & Sawalhi, N. (2011). A new method for separating discrete components from a signal. Sound and Vibration, vol. 45(5), pp. 6.
Seshadrinath, J., Singh, B. & Panigrahi, B. K. (2014). Investigation of Vibration Signatures for Multiple Fault Diagnosis in Variable Frequency Drives Using Complex Wavelets. Power Electronics, IEEE Transactions on, vol. 29(2), pp. 936-945.
Siegel, D., Al-Atat, H., Shauche, V., Liao, L., Snyder, J. & Lee, J. (2012). Novel method for rolling element bearing health assessment—A tachometer-less synchronously averaged envelope feature extraction technique. Mechanical Systems and Signal Processing, vol. 29, pp. 362-376.
Siegel, D., Ly, C. & Lee, J. (2012). Methodology and framework for predicting helicopter rolling element bearing failure. Reliability, IEEE Transactions on, vol. 61(4), pp. 846-857.
Sin, M. L., Soong, W. L. & Ertugrul, N. (2003). Induction machine on-line condition monitoring and fault diagnosis - a survey. Australasian Universities Power Engineering Conference (1-6), Christchurch, New Zealand
Sottile, J., Trutt, F. C. & Kohler, J. L. (2000). Experimental investigation of on-line methods for incipient fault detection [in induction motors]. Industry Applications Conference (2682-2687)
Trutt, F. C., Sottile, J. & Kohler, J. L. (2002). Online condition monitoring of induction motors. Industry Applications, IEEE Transactions on, vol. 38(6), pp. 1627-1632.
Ukil, A., Chen, S. & Andenna, A. (2011). Detection of stator short circuit faults in three-phase induction motors using motor current zero crossing instants. Electric Power Systems Research, vol. 81(4), pp. 1036-1044.
Antoni, J. (2007). Fast computation of the kurtogram for the detection of transient faults. Mechanical Systems and Signal Processing, vol. 21(1), pp. 108-124.
Antoni, J. & Randall, R. (2006). The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mechanical Systems and Signal Processing, vol. 20(2), pp. 308-331.
Bechhoefer, E. & Kingsley, M. (2009). A review of time synchronous average algorithms. Annual conference of the prognostics and health management society
Bell, R., McWilliams, D., O'Donnell, P., Singh, C. & Wells, S. (1985). Report of large motor reliability survey of industrial and commercial installations. I. IEEE Transactions on Industry Applications, vol. 21(4), pp. 853-864.
Cardoso, A. M., Cruz, S. & Fonseca, D. (1999). Inter-turn stator winding fault diagnosis in three-phase induction motors, by Park's vector approach. Energy Conversion, IEEE Transactions on, vol. 14(3), pp. 595-598.
Djurović, S., Vilchis-Rodriguez, D. S. & Smith, A. C. (2014) Investigation of wound rotor induction machine vibration signal under stator electrical fault conditions. The Journal of Engineering.
Eftekhari, M., Moallem, M., Sadri, S. & Hsieh, M.-F. (2013). Online Detection of Induction Motor's Stator Winding Short-Circuit Faults. Systems Journal, IEEE, vol. 8(4), pp. 1272 - 1282. doi: 10.1109/JSYST.2013.2288172
Furfari, F. & Brittain, J. (2002). Charles LeGeyt Fortescue and the method of symmetrical components. Industry Applications Magazine, IEEE, vol. 8(3), pp. 7-9.
Jablonski, A. & Barszcz, T. (2013). Validation of vibration measurements for heavy duty machinery diagnostics. Mechanical Systems and Signal Processing, vol. 38(1), pp. 248-263.
Jabłoński, A., Barszcz, T. & Bielecka, M. (2011). Automatic validation of vibration signals in wind farm distributed monitoring systems. Measurement, vol. 44(10), pp. 1954-1967.
Jardine, A. K., Lin, D. & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, vol. 20(7), pp. 1483-1510.
Jover Rodríguez, P. V. & Arkkio, A. (2008). Detection of stator winding fault in induction motor using fuzzy logic. Applied Soft Computing, vol. 8(2), pp. 1112-1120.
Kliman, G., Premerlani, W., Koegl, R. & Hoeweler, D. (1996). A new approach to on-line turn fault detection in AC motors. Industry Applications Conference, 1996. Thirty-First IAS Annual Meeting, IAS'96., Conference Record of the 1996 IEEE (687-693)
Kliman, G. & Stein, J. (1992). Methods of motor current signature analysis. Electric Machines and power systems, vol. 20(5), pp. 463-474.
Kohler, J. L., Sottile, J. & Trutt, F. C. (2002). Condition monitoring of stator windings in induction motors. I. Experimental investigation of the effective negative-sequence impedance detector. Industry Applications, IEEE Transactions on, vol. 38(5), pp. 1447-1453.
Lamim Filho, P., Pederiva, R. & Brito, J. (2014). Detection of stator winding faults in induction machines using flux and vibration analysis. Mechanical Systems and Signal Processing, vol. 42(1), pp. 377-387.
Lamim, P., Brito, J. N., Silva, V. A. D. & Pederiva, R. (2013). Detection of Electrical Faults in Induction Motors Using Vibration Analysis. Journal of Quality in Maintenance Engineering, vol. 19(4), pp. 2-2.
Lin, J. & Qu, L. (2000). Feature extraction based on Morlet wavelet and its application for mechanical fault diagnosis. Journal of sound and vibration, vol. 234(1), pp. 135-148.
Nandi, S., Toliyat, H. A. & Li, X. (2005). Condition monitoring and fault diagnosis of electrical motors-a review. Energy Conversion, IEEE Transactions on, vol. 20(4), pp. 719-729.
Ompusunggu, A. P., Liu, Z., Ardakani, H. D., Jin, C., Petre, F. & Lee, J. (2014). Winding fault diagnosis of a 3-phase induction motor powered by frequency-inverter drive using the current and voltage signals. Proceedings of the 14th Mechatronics Forum International Conference. June 16-18, Karlstad (Sweden)
Randall, R. B. & Antoni, J. (2011). Rolling element bearing diagnostics—a tutorial. Mechanical Systems and Signal Processing, vol. 25(2), pp. 485-520.
Randall, R. B. & Sawalhi, N. (2011). A new method for separating discrete components from a signal. Sound and Vibration, vol. 45(5), pp. 6.
Seshadrinath, J., Singh, B. & Panigrahi, B. K. (2014). Investigation of Vibration Signatures for Multiple Fault Diagnosis in Variable Frequency Drives Using Complex Wavelets. Power Electronics, IEEE Transactions on, vol. 29(2), pp. 936-945.
Siegel, D., Al-Atat, H., Shauche, V., Liao, L., Snyder, J. & Lee, J. (2012). Novel method for rolling element bearing health assessment—A tachometer-less synchronously averaged envelope feature extraction technique. Mechanical Systems and Signal Processing, vol. 29, pp. 362-376.
Siegel, D., Ly, C. & Lee, J. (2012). Methodology and framework for predicting helicopter rolling element bearing failure. Reliability, IEEE Transactions on, vol. 61(4), pp. 846-857.
Sin, M. L., Soong, W. L. & Ertugrul, N. (2003). Induction machine on-line condition monitoring and fault diagnosis - a survey. Australasian Universities Power Engineering Conference (1-6), Christchurch, New Zealand
Sottile, J., Trutt, F. C. & Kohler, J. L. (2000). Experimental investigation of on-line methods for incipient fault detection [in induction motors]. Industry Applications Conference (2682-2687)
Trutt, F. C., Sottile, J. & Kohler, J. L. (2002). Online condition monitoring of induction motors. Industry Applications, IEEE Transactions on, vol. 38(6), pp. 1627-1632.
Ukil, A., Chen, S. & Andenna, A. (2011). Detection of stator short circuit faults in three-phase induction motors using motor current zero crossing instants. Electric Power Systems Research, vol. 81(4), pp. 1036-1044.
Section
Technical Papers