References
- Bacha, K., Henao, H., Gossa, M. and Capolino, G.-A. (2008). Induction Machine Fault Detection Using Stray Flux EMF Measurement and Neural Network-Based Decision. Electric Power Systems Research, 78(7), pp. 1247–1255.
- Ceban, A., Pusca, R. and Romary, R. (2012). Study of Rotor Faults in Induction Motors Using External Magnetic Field Analysis. IEEE Transactions on Industrial Electronics, 59(5), pp. 2082–2093.
- Ewert, P. (2017). Use of axial flux in the detection of electrical faults in induction motors. In: 2017 International Symposium on Electrical Machines (SME), IEEE, Naleczow, Poland, 18–21 June 2017, pp. 1–6.
- Henao, H., Capolino, G.-A., Fernandez-Cabanas, M., Filippetti, F., Bruzzese, C., Strangas, E. and Hedayati-Kia, S. (2014). Trends in Fault Diagnosis for Electrical Machines: A Review of Diagnostic Techniques. IEEE Industrial Electronics Magazine, 8(2), pp. 31–42.
- Jung, J. H., Lee, J.-J. and Kwon, B.-H. (2006). Online Diagnosis of Induction Motors Using MCSA. IEEE Transactions on Industrial Electronics, 53(6), pp. 1842–1852.
- Kowalski, C. T. and Orlowska-Kowalska, T. (2003). Neural Networks Application for Induction Motor Faults Diagnosis. Mathematics and Computers in Simulation, 63(3–5), pp. 435–448.
- Meshgin-Kelk, H., Milimonfared, J. and Toliyat, H. A. (2004). Interbar Currents and Axial Fluxes in Healthy and Faulty Induction Motors. IEEE Transactions on Industry Applications, 40(1), pp. 128–134.
- Morsalin, S., Mahmud, K., Mohiuddin, H., Halim, M. R. and Saha, P. (2014). Induction motor inter-turn fault detection using heuristic noninvasive approach by artificial neural network with Levenberg Marquardt algorithm. In: 2014 International Conference on Informatics, Electronics & Vision (ICIEV). Dhaka, Bangladesh, 23–24 May 2014, pp. 1–6. Available at: https://ieeexplore.ieee.org/document/7136002.
- Orłowska-Kowalska, T. and Dybkowski, M. (2016). Industrial Drive Systems. Current State and Development Trends. Power Electronics and Drives, 1(36)(1), pp. 5–25.
- Penman, J., Sedding, H. G., Lloyd, B. A. and Fink, W. T. (1994). Detection and Location of Interturn Short Circuits in the Stator Windings of Operating Motors. IEEE Transactions on Energy Conversion, 9(4), pp. 652–658.
- Pietrowski, W. (2011). Application of Radial Basis Neural Network to Diagnostics of Induction Motor Stator Faults Using Axial Flux. Przegląd Elektrotechniczny (Electrical Review), R. 87 NR 6/2011, pp. 190–192.
- Rama Krishna, M. S. and Kishan, S. H. (2013). Neural network for the diagnosis of rotor broken faults of induction motors using MCSA. In: 7th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, India, 4–5 January 2013, pp. 133–137. Available at: https://ieeexplore.ieee.org/document/6481136.
- Romary, R., Pusca, R., Lecointe, J. P. and Brudny, J. F. (2013). Electrical machines fault diagnosis by stray flux analysis. In: 2013 IEEE Workshop on Electrical Machines Design, Control and Diagnosis (WEMDCD), Paris, France, 11–12 March 2013, pp. 247–256. Available at: https://ieeexplore.ieee.org/document/6525184.
- Toni, K., Slobodan, M. and Aleksandar, B. (2007). Detection of turn to turn faults in stator winding with axial magnetic flux in induction motors. In: IEEE International Conference on Electric Machines and Drives, Antalya, Turkey, 3–5 May 2007, pp. 826–829. Available at: https://ieeexplore.ieee.org/document/4270748.
- Tulicki, J., Petryna, J. and Sułowicz, M. (2016). Fault Diagnosis of Induction Motors in Selected Working Conditions Based on Axial Flux Signals. Technical Transactions, 13(Electrical Engineering, 3–E), pp. 99–113.
- Vas, P. (1993). Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines. Oxford: Oxford University Press.
- Vas, P. (1999). Artificial Intelligence-Based Electrical Machines and Drives: Applications of Fuzzy, Neural, Fuzzy-Neural and Genetic Algorithm Based Techniques. Oxford: Oxford University Press.
- Wolkiewicz, M. and Kowalski, C. T. (2016). Incipient stator fault detector based on neural networks and symmetrical components analysis for induction motor drives. In: 2016 13th Selected Issues of Electrical Engineering and Electronics (WZEE), IEEE, Rzeszow, Poland, 4–8 May 2016, pp. 1–7.
- Wolkiewicz, M. and Skowron, M. (2017). Diagnostic system for induction motor stator winding faults based on axial flux. Power Electronics and Drives, 2(37)(2), pp. 137–150.
- Wolkiewicz, M., Tarchała, G. and Kowalski, C. T. (2015). Stator Windings Condition Diagnosis of Voltage Inverter-Fed Induction Motor in Open and Closed-Loop Control Structures. Archives of Electrical Engineering, 64(1), pp. 67–79.