A Study on the Characteristic of Stator Winding Degradation Process and Its Life Estimation of Induction Motors
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Published
Jul 14, 2017
Viethung Nguyen
Danwei Wang
Jeevanand Seshadrinath
Abhisek Ukil
Vinay Jaiswal
Nishant Verma
Viswanathan Vaiyapuri
Sivakumar Nadarajan
Abstract
This paper presents an analysis on the characteristics of the stator winding degradation process. A diagnostic and prognostic parameter, which is derived using the sequence component approach, is proposed. It is estimated using only the measurements of voltages and currents, which are easily obtained, and hence, the method can be implemented in real-time applications. A test is designed for generating stator winding inter-turn fault and accelerating it. The characteristic of the degradation process based on the prognostic parameter is discussed. The collected data is modeled and the remaining useful life (RUL) is estimated.
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Keywords
PHM
References
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Kallesoe, C. S., Vadstrup, P., Rasmussen, H., & Izadi- Zamanabadi, R. (2004). Estimation of stator winding faults in induction motors using an adaptive observer scheme. Conference Record of the IEEE IAS Annual Meeting, vol. 2, pp. 1225-1232.
Bachir, S., Tnani, S., Trigeassou, J. C., & Champenois, G. (2006). Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines. IEEE Transactions on Industrial Electronics, vol. 53, no. 33, pp. 963-973.
Nguyen, V. H., Wang, D. W., Ukil, A., Nadarajan, S., Vaiyapuri, V., & Jayampathi, C. (2015). A closed-form solution to fault parameter estimation and faulty phase identification of stator winding inter-turn fault in induction machines. Annual Conference of the IEEE Industrial Electronics Society, pp. 286-291.
Nguyen, V. H., Wang, D. W., Seshadrinath, J., Nadarajan, S., & Vaiyapuri, V. (2016). Fault severity estimation using nonlinear Kalman filter for induction motors under inter-turn fault. Annual Conference of the IEEE Industrial Electronics Society, pp. 1488-1493.
Sharp, M. E. (2012). Prognostic approaches using transient monitoring methods. Doctoral dissertation. University of Tennessee, USA.
Erbay, A. S. (1999). Multi-sensor Fusion for Induction motor aging analysis and fault diagnosis. Doctoral dissertation. University of Tennessee, USA.
De Angelo, C. H., Bossio, G. R., Giaccone, S. J., Valla, M. I., Solsona, J. A., & Garcia, G. O. (2009). Online model-based stator-fault detection and identification in induction motors. IEEE Transactions on Industrial Electronics, vol. 56, no. 11, pp. 4671-4680.
Saxena, A., Goebel, K., Simon, D., & Eklund, N. (2008). Damage propagation modeling for aircraft engine runto-failure simulation. International Conference on Prognostics and Health Management, pp. 1-9.
Babel, A. S., & Strangas, E. G. (2014, September). Condition-based monitoring and prognostic health management of electric machine stator winding insulation. IEEE International Conference on Electrical Machines, pp. 1855-1861.
Han, Y., & Song, Y. H. (2003). Condition monitoring techniques for electrical equipment-a literature survey. IEEE Transactions on Power delivery, vol. 18, no. 1, pp. 4-13.
Kallesoe, C. S., Vadstrup, P., Rasmussen, H., & Izadi- Zamanabadi, R. (2004). Estimation of stator winding faults in induction motors using an adaptive observer scheme. Conference Record of the IEEE IAS Annual Meeting, vol. 2, pp. 1225-1232.
Bachir, S., Tnani, S., Trigeassou, J. C., & Champenois, G. (2006). Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines. IEEE Transactions on Industrial Electronics, vol. 53, no. 33, pp. 963-973.
Nguyen, V. H., Wang, D. W., Ukil, A., Nadarajan, S., Vaiyapuri, V., & Jayampathi, C. (2015). A closed-form solution to fault parameter estimation and faulty phase identification of stator winding inter-turn fault in induction machines. Annual Conference of the IEEE Industrial Electronics Society, pp. 286-291.
Nguyen, V. H., Wang, D. W., Seshadrinath, J., Nadarajan, S., & Vaiyapuri, V. (2016). Fault severity estimation using nonlinear Kalman filter for induction motors under inter-turn fault. Annual Conference of the IEEE Industrial Electronics Society, pp. 1488-1493.
Sharp, M. E. (2012). Prognostic approaches using transient monitoring methods. Doctoral dissertation. University of Tennessee, USA.
Erbay, A. S. (1999). Multi-sensor Fusion for Induction motor aging analysis and fault diagnosis. Doctoral dissertation. University of Tennessee, USA.
De Angelo, C. H., Bossio, G. R., Giaccone, S. J., Valla, M. I., Solsona, J. A., & Garcia, G. O. (2009). Online model-based stator-fault detection and identification in induction motors. IEEE Transactions on Industrial Electronics, vol. 56, no. 11, pp. 4671-4680.
Saxena, A., Goebel, K., Simon, D., & Eklund, N. (2008). Damage propagation modeling for aircraft engine runto-failure simulation. International Conference on Prognostics and Health Management, pp. 1-9.
Babel, A. S., & Strangas, E. G. (2014, September). Condition-based monitoring and prognostic health management of electric machine stator winding insulation. IEEE International Conference on Electrical Machines, pp. 1855-1861.
Section
Regular Session Papers