Implementation of Wavelet Packet Transform for Detection and Analysis of Stator Faults in Induction Machine
- 1 Department of Electronics and Electronics Engineering, Adithya Institute of Technology, Coimbatore, India
- 2 Principal Maharaja Institute of Technology, Coimbatore, India
- 3 SriGuru Institute of Technology, Coimbatore, India
- 4 Department of Electrical & Electronics Engineering, PPG Institute of Technology, Coimbatore, India
Abstract
Execution of an online detection technique for induction motor fault diagnosis and research at the current period of time is discussed in this paper. Wavelet packets transform (WPT)-based algorithm is used by the detection method for investigating and identification of many disruptions that happen in three-phase induction motors. The association of the coefficients of the WPT of line currents with the help of a main wavelet at the secondary level of resolution with a threshold discovered through an experiment at the time of the vital position can used to observe the motor reference point. The propagation of wavelet analysis and disintegration of the signal into an equivalent bandwidth which can attain a good disintegration of the solution than what wavelet analysis do is called as Wavelet packet analysis. In order to overcome accidental failing, the on-line fault diagnostics technology for the reduction of incipient errors is a must.
- Tavner, P.J. and Penman, J. (1987) Condition Monitoring of Electrical Machines. Research Studies Press, Letchworth.
- Zhang, P., Du, Y., Habetler, T.G. and Lu, B. (2011) A Survey of Condition Monitoring and Protection Methods for Medium-Voltage Induction Motors. IEEE Transactions on Industry Applications, 47, 34-46. http://dx.doi.org/10.1109/TIA.2010.2090839
- Benbouzid, M.E.H. (2000) A Review of Induction Motors Signature Analysis as a Medium for Faults Detection. IEEE Transactions on Industrial Electronics, 47, 984-992. http://dx.doi.org/10.1109/41.873206
- Trzynadlowski, A.J. and Ritchie, E. (2000) Comparative Investigation of Diagnostic Media for Induction Motors: A Case of Rotor Cage Faults. IEEE Transactions on Industrial Electronics, 47, 1092-1099. http://dx.doi.org/10.1109/41.873218
- Trutt, F.C., Sottile, J. and Kohler, J.L. (2002) Online Condition Monitoring of Induction Motors. IEEE Transactions on Industry Applications, 38, 1627-1632. http://dx.doi.org/10.1109/TIA.2002.804758
- Douglas, H., Pillay, P. and Ziarani, A.K. (2005) Broken Rotor Bar Detection in Induction Machines with Transient Operating Speeds. IEEE Transactions on Energy Conversion, 20, 135-141. http://dx.doi.org/10.1109/TEC.2004.842394
- Said, M.S.N., Benbouzid, M.E.H. and Benchaib, A. (2000) Detection of Broken Bars in Induction Motors Using an Extended Kalman Filter for Rotor Resistance Sensorless Estimation. IEEE Transactions on Energy Conversion, 15, 66- 70. http://dx.doi.org/10.1109/60.849118
- Ethny, S., Acarnley, P.P., Zahawi, B. and Giaouris, D. (2006) Induction Machine Fault Identification Using Particle Swarm Algorithms. IEEE International Conference on Power Electronics, Drives and Energy Systems for Industrial Growth (PEDES 2006), New Delhi. http://dx.doi.org/10.1109/PEDES.2006.344310
- Ethni, S.A., Zahawi, B., Giaouris, D. and Acarnley, P.P. (2009) Comparison of Particle Swarm and Simulated Annealing Algorithms for Induction Motor Fault Identification. 7th IEEE International Conference on Industrial Informatics (INDIN 2009), Cardiff, June 2009, 470-474. http://dx.doi.org/10.1109/INDIN.2009.5195849
- Ethni, S.A., Gadoue, S. and Zahawi, B. (2014) Induction Machine Winding Faults Identification Using Bacterial Foraging Optimization. 7th IET International Conference on Power Electronics, Machines and Drives (PEMD), Manchester. http://dx.doi.org/10.1049/cp.2014.0298
- Alamyal, M., Gadoue, S.M. and Zahawi, B. (2013) Detection of Induction Machine Winding Faults Using Genetic Algorithm. 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED 2013), Valencia, August 2013, 157-161. http://dx.doi.org/10.1109/DEMPED.2013.6645711