References
[1]. Aharon, M., Elad, M., & Bruckstein, A. (2006). K-SVD: An algorithm for designing over complete dictionaries for sparse representation. IEEE Transactions on signal processing, 54(11), 4311-4322. https://doi.org/10.1109/ TSP.2006.881199
[2]. Alameh, K., Cité, N., Hoblos, G., & Barakat, G. (2015, April). Feature extraction for vibration-based fault detection in Permanent Magnet Synchronous Motors. In 2015, Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE) (pp. 163-168). IEEE. https://doi.org/ 10.1109/TAEECE.2015.7113620
[3]. Cabal-Yepez, E., Garcia-Ramirez, A. G., Romero- Troncoso, R. J., Garcia-Perez, A., & Osornio-Rios, R. A. (2012). Reconfigurable monitoring system for timefrequency analysis on industrial equipment through STFT and DWT. IEEE Transactions on Industrial Informatics, 9(2), 760-771. https://doi.org/10.1109/TII.2012.2221131
[4]. Chen, F., Tang, B., & Chen, R. (2013). A novel fault diagnosis model for gearbox based on wavelet support vector machine with immune genetic algorithm. Measurement, 46(1), 220-232. https://doi.org/10.1016/j. measurement.2012.06.009
[5]. Chen, Z., & Li, W. (2017). Multisensor feature fusion for bearing fault diagnosis using sparse autoencoder and deep belief network. IEEE Transactions on Instrumentation and Measurement, 66(7), 1693-1702. https://doi.org/10. 1109/TIM.2017.2669947
[6]. Chen, Z., & Li, W. (2017). Multisensor feature fusion for bearing fault diagnosis using sparse auto encoder and Deep Belief Network. IEEE Transaction, Instrumentation and Measurement. 66, 1693–1702.
[7]. Cheng, M., Chau, K. T., Chan, C. C., Zhou, E., & Huang, X. (2000). Nonlinear varying-network magnetic circuit analysis for doubly salient permanent-magnet motors. IEEE Transactions on Magnetics, 36(1), 339-348. https://doi.org/10.1109/20.822544
[8]. Çira, F., Arkan, M., & Gümüş, B. (2015, September). A new approach to detect stator fault in permanent magnet synchronous motors. In 2015, IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) (pp. 316-321). IEEE. https://doi.org/10.1109/DEMPED.2015.73 03708
[9]. Cira, F., Arkan, M., Gümüş, B., & Goktas, T. (2016, October). Analysis of stator inter-turn short-circuit fault signatures for inverter-fed permanent magnet synchronous motors. In IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society (pp. 1453-1457). IEEE.
[10]. Dou, R., Song, F., Liu, H., & Men, X. (2018, October). Demagnetization quantification of pmsm based on support vector regression. In 2018, Prognostics and System Health Management Conference (PHMChongqing) (pp. 619-623). IEEE. https://doi.org/10.1109/ PHM-Chongqing.2018.00111
[11]. Ebrahimi, B. M., Faiz, J., Javan-Roshtkhari, M., & Nejhad, A. Z. (2008). Static eccentricity fault diagnosis in permanent magnet synchronous motor using time stepping finite element method. IEEE Transactions on Magnetics, 44(11), 4297-4300. https://doi.org/10.1109/ TMAG.2008.2001534
[12]. Ebrahimi, B. M., Roshtkhari, M. J., Faiz, J., & Khatami, S. V. (2013). Advanced eccentricity fault recognition in permanent magnet synchronous motors using stator current signature analysis. IEEE Transactions on Industrial Electronics, 61(4), 2041-2052. https://doi.org/10.1109/ TIE.2013.2263777
[13]. Elbouchikhi, E., Choqueuse, V., Auger, F., & Benbouzid, M. E. H. (2017). Motor current signal analysis based on a matched subspace detector. IEEE Transactions on Instrumentation and Measurement, 66(12), 3260-3270. https://doi.org/10.1109/TIM.2017.27 49858
[14]. Espinosa, A. G., Rosero, J. A., Cusido, J., Romeral, L., & Ortega, J. A. (2010). Fault detection by means of Hilbert–Huang transform of the stator current in a PMSM with demagnetization. IEEE Transactions on Energy Conversion, 25(2), 312-318. https://doi.org/10.1109/TEC. 2009.2037922
[15]. Faiz, J., & Exiri, S. A. H. (2015, September). Shortcircuit fault diagnosis in permanent magnet synchronous motors-an overview. In 2015, Intl Aegean Conference on Electrical Machines & Power Electronics (ACEMP), 2015 Intl Conference on Optimization of Electrical & Electronic Equipment (OPTIM) & 2015 Intl Symposium on Advanced Electromechanical Motion Systems (ELECTROMOTION) (pp. 18-27). IEEE. https://doi.org/10.1109/OPTIM.2015.74 27038
[16]. Faiz, J., Ghorbanian, V., & Ebrahimi, B. M. (2012, December). A new criterion for rotor broken bar fault diagnosis in line-start and inverter-fed induction motors using Hilbert-Huang transform. In 2012, IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) (pp. 1-6). IEEE. https://doi.org/10.1109/ PEDES.2012.6484397
[17]. Faiz, J., Nejadi-Koti, H., & Exiri, A. H. (2017). Inductance-based inter-turn fault detection in permanent magnet synchronous machine using magnetic equivalent circuit model. Electric Power Components and Systems, 45(9), 1016-1030.
[18]. Faiz, J., Nejadi-Koti, H., & Exiri, A. H. (2017). Inductance-based inter-turn fault detection in permanent magnet synchronous machine using magnetic equivalent circuit model. Electric Power Components and Systems, 45(9), 1016-1030. https://doi. org/10.1080/15325008.2017.1293196
[19]. Filippetti, F., Franceschini, G., Tassoni, C., & Vas, P. (2000). Recent developments of induction motor drives fault diagnosis using AI techniques. IEEE Transactions on Industrial Electronics, 47(5), 994-1004. https://doi.org/10. 1109/41.873207
[20]. Fitouri, M., BenSalem, Y., & Abdelkrim, M. N. (2016, March). Analysis and co-simulation of permanent magnet sychronous motor with short-circuit fault by finite th element method. In 2016, 13 International Multi- Conference on Systems, Signals & Devices (SSD) (pp. 472- 477). IEEE. https://doi.org/10.1109/SSD.2016.7473721
[21]. Goktas, T., Zafarani, M., & Akin, B. (2015, May). Separation of broken magnet and static eccentricity failures in PMSM. In 2015, IEEE International Electric Machines & Drives Conference (IEMDC) (pp. 1459-1465). IEEE. https://doi.org/10.1109/IEMDC.2015.7409254
[22]. Gritli, Y., Rossi, C., Casadei, D., Zarri, L., & Filippetti, F. (2012, September). Demagnetizations diagnosis for permanent magnet synchronous motors based on advanced wavelet analysis. In 2012, XXth International Conference on Electrical Machines (pp. 2397-2403). IEEE. https://doi.org/10.1109/ICElMach.2012.6350219
[23]. Guefack, F. L. T., Kiselev, A., & Kuznietsov, A. (2018, June). Improved detection of inter-turn short circuit faults in PMSM drives using principal component analysis. In 2018, International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) (pp. 154-159). IEEE. https://doi.org/10.1109/SPEEDAM.2018. 8445403
[24]. Haddad, R. Z., & Strangas, E. G. (2016). On the accuracy of fault detection and separation in permanent magnet synchronous machines using MCSA/MVSA and LDA. IEEE Transactions on Energy Conversion, 31(3), 924- 934. https://doi.org/10.1109/TEC.2016.2558183
[25]. Hang, J., Ding, S., Zhang, J., Cheng, M., Chen, W., & Wang, Q. (2016). Detection of interturn short-circuit fault for PMSM with simple fault indicator. IEEE Transactions on Energy Conversion, 31(4), 1697-1699. https://doi.org/10. 1109/TEC.2016.2583780
[26]. Hang, J., Zhang, J., & Cheng, M. (2016). Detection and discrimination of open phase fault in permanent magnet synchronous motor drive system. IEEE Transaction & Power Electronics, 31, 4697–4709.
[27]. Hassani, H., Zarei, J., Arefi, M. M., & Razavi-Far, R. (2017). zSlices-based general type-2 fuzzy fusion of support vector machines with application to bearing fault detection. IEEE Transactions on Industrial Electronics, 64(9), 7210-7217. https://doi.org/10.1109/TIE.2017.268 8963
[28]. Hou, J., Wang, Y., Gao, T., & Yang, Y. (2016, September). Fault feature extraction of power electronic circuits based on sparse decomposition. In 2016, International Conference on Condition Monitoring and Diagnosis (CMD) (pp. 505-508). IEEE. https://doi.org/10. 1109/CMD.2016.7757872
[29]. Immovilli, F., Bianchini, C., Cocconcelli, M., Bellini, A., & Rubini, R. (2012). Bearing fault model for induction motor with externally induced vibration. IEEE Transactions on Industrial Electronics, 60(8), 3408-3418. https://doi. org/10.1109/TIE.2012.2213566
[30]. Ince, T., Kiranyaz, S., Eren, L., Askar, M., & Gabbouj, M. (2016). Real-time motor fault detection by 1-D convolutional neural networks. IEEE Transactions on Industrial Electronics, 63(11), 7067-7075. https://doi.org/ 10.1109/TIE.2016.2582729
[31]. Ishikawa, T., Seki, Y., & Kurita, N. (2013). Analysis for fault detection of vector-controlled permanent magnet synchronous motor with permanent magnet defect. IEEE Transactions on Magnetics, 49(5), 2331-2334. https://doi. org/10.1109/TMAG.2013.2243135
[32]. Jiangting, L. I. U., Kaifeng, Z. H. O. U., & Yue, H. U. (2018, September). EMD-WVD method based highfrequency current analysis of low voltage arc. In 2018, Condition Monitoring and Diagnosis (CMD) (pp. 1-5). IEEE. https://doi.org/10.1109/CMD.2018.8535969
[33]. Jokic, S., Cincar, N., & Novakovic, B. (2018, March). The analysis of vibration measurement and current signature in motor drive faults detection. In 2018, 17th International Symposium Infoteh-Jahorina (INFOTEH) (pp. 1- 6). IEEE. https://doi.org/10.1109/INFOTEH.2018.8345531
[34]. Kalimov, A., & Shimansky, S. (2015). Optimal design of the synchronous motor with the permanent magnets on the rotor surface. IEEE Transactions on Magnetics, 51(3), 1-4. https://doi.org/10.1109/TMAG.2014.2362961
[35]. Kao, I. H., Wang, W. J., Lai, Y. H., & Perng, J. W. (2018). Analysis of permanent magnet synchronous motor fault diagnosis based on learning. IEEE Transactions on Instrumentation and Measurement, 68(2), 310-324. https://doi.org/10.1109/TIM.2018.2847800
[36]. Karami, M., Mariun, N., Mehrjou, M. R., AbKadir, M. Z. A., Misron, N., & Radzi, M. A. M. (2014, December). Diagnosis of static eccentricity fault in line start permanent magnet synchronous motor. In 2014, IEEE International Conference on Power and Energy (PECon) (pp. 83-86). IEEE.
[37]. Khan, M. S., Okonkwo, U. V., Usman, A., & Rajpurohit, B. S. (2018, August). Finite element modeling of demagnetization fault in permanent magnet direct current motors. In 2018, IEEE Power & Energy Society General Meeting (PESGM) (pp. 1-5). IEEE. https://doi.org/ 10.1109/PESGM.2018.8586622
[38]. Kim, K. C., Lim, S. B., Koo, D. H., & Lee, J. (2006). The shape design of permanent magnet for permanent magnet synchronous motor considering partial demagnetization. IEEE Transactions on Magnetics, 42(10), 3485-3487.
[39]. Kim, K. H. (2010). Simple online fault detecting scheme for short-circuited turn in a PMSM through current harmonic monitoring. IEEE Transactions on Industrial Electronics, 58(6), 2565-2568.
[40]. Li, H., & Zhang, Y. (2006, June). Bearing faults diagnosis based on EMD and Wigner-Ville distribution. In 2006, 6th World Congress on Intelligent Control and Automation (Vol. 2, pp. 5447-5451). IEEE. https://doi.org/ 10.1109/WCICA.2006.1714113
[41]. Li, Y., & Liang, Y. (2015, August). A comparative study on inter-tern short circuit fault of PMSM using finite element analysis and experiment. In 2015, International Conference on Advanced Mechatronic Systems (ICAMechS) (pp. 290-294). IEEE. https://doi.org/10.1109/ ICAMechS.2015.7287076
[42]. Liang, H., Chen, Y., Liang, S., & Wang, C. (2018). Fault detection of stator inter-turn short-circuit in PMSM on stator current and vibration signal. Applied Sciences, 8(9), 1677. https://doi.org/10.3390/app8091677
[43]. Liang, S., Chen, Y., Liang, H., Li, X. Sparse Representation and SVM Diagnosis Method for Inter-Turn Short-Circuit Fault in PMSM. Applied Sciences, 2019, 9(2), 224. https://doi.org/10.3390/app9020224
[44]. Liang, Y. (2014, February). Diagnosis of inter-turn short-circuit stator winding fault in PMSM based on stator current and noise. In 2014, IEEE International Conference on Industrial Technology (ICIT) (pp. 138-142). IEEE. https:// doi.org/10.1109/ICIT.2014.6894927
[45]. Lu, C., Wang, Y., Ragulskis, M., & Cheng, Y. (2016). Fault diagnosis for rotating machinery: A method based on image processing. PloS one, 11(10). https://doi.org/ 10.1371/journal.pone.0164111
[46]. Luo, Y., Qiu, J., & Shi, C. (2018, October). Fault Detection of permanent magnet synchronous motor st based on deep learning method. In 2018, 21 International Conference on Electrical Machines and Systems (ICEMS) (pp. 699-703). IEEE. https://doi.org/10. 23919/ICEMS.2018.8549129
[47]. Mallat, S. G., & Zhang, Z. (1993). Matching pursuits with time-frequency dictionaries. IEEE Transactions on Signal Processing, 41(12), 3397-3415. https://doi.org/10. 1109/78.258082
[48]. Marcic, T., Stumberger, B., Stumberger, G., Hadziselimovic, M., Virtic, P., & Dolinar, D. (2008). Linestarting three-and single-phase interior permanent magnet synchronous motors—Direct comparison to induction motors. IEEE Transactions on Magnetics, 44(11), 4413-4416. https://doi.org/10.1109/TMAG.2008.2001537
[49]. Mazzoletti, M. A., Bossio, G. R., De Angelo, C. H., & Espinoza-Trejo, D. R. (2017). A model-based strategy for interturn short-circuit fault diagnosis in PMSM. IEEE Transactions on Industrial Electronics, 64(9), 7218-7228. https://doi.org/10.1109/TIE.2017.2688973
[50]. Mehrjou, M. R., Mariun, N., Karami, M., Misron, N., & Radzi, M. A. M. (2015). Statistical features analysis of transient current signal for broken bars fault detection in rd LS-PMSMs. In Proceedings of the 2015 IEEE 3 International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA), Kuala Lumpur, Malaysia (pp. 1–6).
[51]. Moosavi, S. S., Djerdir, A., Aït-Amirat, Y., & Kkuburi, D. A. (2012, September). Artificial neural networks based fault detection in 3-Phase PMSM traction motor. In 2012, XXth International Conference on Electrical Machines (pp. 1579-1585). IEEE. https://doi.org/10.1109/ICElMach. 2012.6350089
[52]. Moosavi, S. S., Esmaili, Q., Djerdir, A., & Amirat, Y. A. (2017, December). Inter-turn fault detection in stator winding of PMSM using wavelet transform. In 2017, IEEE Vehicle Power and Propulsion Conference (VPPC) (pp. 1- 5). IEEE. https://doi.org/10.1109/VPPC.2017.8330891
[53]. Nandi, S., Toliyat, H. A., & Li, X. (2005). Condition monitoring and fault diagnosis of electrical motors—A review. IEEE Transactions on Energy Conversion, 20(4), 719-729.
[54]. Nedjar, B., Vido, L., Hlioui, S., Amara, Y., & Gabsi, M. (2012, May). Hybrid coupling: Magnetic equivalent circuit coupled to finite element analysis for PMSM electromagnetic modeling. In 2012, IEEE International Symposium on Industrial Electronics (pp. 858-862). IEEE. https://doi.org/10.1109/ISIE.2012.6237201
[55]. Niu, X., Zhu, L., & Ding, H. (2005). New statistical moments for the detection of defects in rolling element bearings. The International Journal of Advanced Manufacturing Technology, 26(11-12), 1268-1274. https://doi.org/10.1007/s00170-004-2109-4
[56]. Obeid, N. H., Battiston, A., Boileau, T., & Nahid- Mobarakeh, B. (2017). Early intermittent interturn fault detection and localization for a permanent magnet synchronous motor of electrical vehicles using wavelet transform. IEEE Transactions on Transportation Electrification, 3(3), 694-702. https://doi.org/10.1109/TTE. 2017.2743419
[57]. Obeid, N. H., Boileau, T., & Nahid-Mobarakeh, B. (2016). Modeling and diagnostic of incipient interturn faults for a three-phase permanent magnet synchronous motor. IEEE Transactions on Industry Applications, 52(5), 4426-4434. https://doi.org/10.1109/TIA.2016.2581760
[58]. Pati, Y. C., Rezaiifar, R., & Krishnaprasad, P. S. (1993, November). Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition. In Proceedings of 27th Asilomar conference on signals, systems and computers (pp. 40- 44). IEEE. https://doi.org/10.1109/ACSSC.1993.342465
[59]. Peter, H., & Hahn, I. (2012, June). Model based rotor angle fault detection in PM synchronous machines. In International Symposium on Power Electronics Power Electronics, Electrical Drives, Automation and Motion (pp. 44-49). IEEE. https://doi.org/10.1109/SPEEDAM.2012. 6264376
[60]. Ping, Z. A., Juan, Y., & Ling, W. (2013, January). Fault detection of stator winding interturn short circuit in PMSM based on wavelet packet analysis. In 2013, Fifth International Conference on Measuring Technology and Mechatronics Automation (pp. 566-569). IEEE. https://doi. org/10.1109/ICMTMA.2013.141
[61]. Quiroga, J., Cartes, D. A., Edrington, C. S., & Liu, L. (2008, September). Neural network based fault detection of PMSM stator winding short under load fluctuation. In th 2008, 13 International Power Electronics and Motion Control Conference (pp. 793-798). IEEE. https://doi.org/ 10.1109/EPEPEMC.2008.4635364
[62]. Quiroga, J., Liu, L., & Cartes, D. A. (2008, June). Fuzzy logic based fault detection of PMSM stator winding short under load fluctuation using negative sequence analysis. In 2008, American Control Conference (pp. 4262-4267). IEEE. https://doi.org/10.1109/ACC.2008.4587163
[63]. Refaat, S. S., Abu-Rub, H., Saad, M. S., Aboul-Zahab, E. M., & Iqbal, A. (2013, May). Discrimination of stator winding turn fault and unbalanced supply voltage in permanent magnet synchronous motor using ANN. In 4th International Conference on Power Engineering, Energy and Electrical Drives (pp. 858-863). IEEE. https://doi.org/ 10.1109/PowerEng.2013.6635722
[64]. Ren, L., Lv, W., Jiang, S., & Xiao, Y. (2016). Fault diagnosis using a joint model based on sparse representation and SVM. IEEE Transactions on Instrumentation and Measurement, 65(10), 2313-2320. https://doi.org/10.1109/TIM.2016.2575318
[65]. Romeral, L., Urresty, J. C., Ruiz, J. R. R., & Espinosa, A. G. (2010). Modeling of surface-mounted permanent magnet synchronous motors with stator winding interturn faults. IEEE Transactions on Industrial Electronics, 58(5), 1576-1585. https://doi.org/10.1109/TIE.2010.2062480
[66]. Rosero, J. A., Cusido, J., Garcia, A., Ortega, J. A., & Romeral, L. (2006, November). Broken bearings and eccentricity fault detection for a permanent magnet nd synchronous motor. In IECON 2006-32 Annual Conference on IEEE Industrial Electronics (pp. 964-969). IEEE. https://doi.org/10.1109/IECON.2006.347599
[67]. Rosero, J. A., Romeral, L., Cusido, J., Garcia, A., & Ortega, J. A. (2007, June). On the short-circuiting fault detection in a PMSM by means of stator current transformations. In 2007, IEEE Power Electronics Specialists Conference (pp. 1936-1941). IEEE. https://doi. org/10.1109/PESC.2007.4342300
[68]. Rosero, J. A., Romeral, L., Ortega, J. A., & Rosero, E. (2009). Short-circuit detection by means of empirical mode decomposition and Wigner–Ville distribution for PMSM running under dynamic condition. IEEE Transactions on Industrial Electronics, 56(11), 4534-4547. https://doi.org/10.1109/TIE.2008.2011580
[69]. Rosero, J., Cusido, J., Espinosa, A. G., Ortega, J. A., & Romeral, L. (2007, June). Broken bearings fault detection for a permanent magnet synchronous motor under non-constant working conditions by means of a joint time frequency analysis. In 2007, IEEE International Symposium on Industrial Electronics (pp. 3415-3419). IEEE. https://doi.org/10.1109/ISIE.2007.4375165
[70]. Rosero, J., Romeral, L., Cusido, J., & Ortega, J. A. (2007, November). Fault detection by means of wavelet transform in a PMSMW under demagnetization. In IECON rd 2007-33 Annual Conference of the IEEE Industrial Electronics Society (pp. 1149-1154). IEEE. https://doi.org/ 10.1109/IECON.2007.4460323
[71]. Rosero, J., Romeral, L., Ortega, J. A., &Rosero, E. (2008, February). Short circuit fault detection in PMSM by means of empirical mode decomposition (EMD) and wignerville distribution (WVD). In 2008, Twenty-Third Annual IEEE Applied Power Electronics Conference and Exposition (pp. 98-103). IEEE. https://doi.org/10.1109/ APEC.2008.4522706
[72]. Rosero, J., Romeral, L., Rosero, E., &Urresty, J. (2009, February). Fault Detection in dynamic conditions by means of Discrete Wavelet Decomposition for PMSM running under Bearing Damage. In 2009, Twenty-Fourth Annual IEEE Applied Power Electronics Conference and Exposition (pp. 951-956). IEEE. https://doi.org/10.1109/ APEC.2009.4802777
[73]. Ruoho, S., Kolehmainen, J., Ikaheimo, J., & Arkkio, A. (2009). Interdependence of demagnetization, loading, and temperature rise in a permanent-magnet synchronous motor. IEEE Transactions on Magnetics, 46(3), 949-953. https://doi.org/10.1109/TMAG.2009.203 3592
[74]. Ruoho, S., Kolehmainen, J., Ikaheimo, J., & Arkkio, A. (2009). Interdependence of demagnetization, loading, and temperature rise in a permanent-magnet synchronous motor. IEEE Transactions on Magnetics, 46(3), 949-953. https://doi.org/10.1109/TMAG.2009.2033 592
[75]. Safizadeh, M. S., & Latifi, S. K. (2014). Using multisensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell. Information Fusion, 18, 1-8. https://doi.org/10.1016/j. inffus.2013.10.002
[76]. Schmidhuber, J. (2015). Deep learning in neural networks: An overview. Neural Networks, 61, 85-117. https://doi.org/10.1016/j.neunet.2014.09.003
[77]. Siddiqui, K. M., Sahay, K., & Giri, V. K. (2014). Health monitoring and fault diagnosis in induction motor-a review. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(1), 6549-6565.
[78]. Siddiqui, K. M., Sahay, K., & Giri, V. K. (2017). Modeling and open phase fault analysis in three and five phase permanent magnet synchronous motor machine. i-Manager's Journal on Instrumentation & Control Engineering, 5(4), 32-40. https://doi.org/10.26634/jic.5. 4.13843
[79]. Stack, J. R., Harley, R. G., & Habetler, T. G. (2004). An amplitude modulation detector for fault diagnosis in rolling element bearings. IEEE Transactions on Industrial Electronics, 51(5), 1097-1102.
[80]. Strangas, E. G., Aviyente, S., & Zaidi, S. S. H. (2008). Time–frequency analysis for efficient fault diagnosis and failure prognosis for interior permanent-magnet AC motors. IEEE Transactions on Industrial Electronics, 55(12), 4191-4199. https://doi.org/10.1109/TIE.2008.2007529
[81]. Urresty, J., Riba, J., Romeral, L., Rosero, J., & Serna, J. (2009, August). Stator short circuits detection in PMSM by means of Hilbert-Huang transform and energy calculation. In 2009, IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (pp. 1-7). IEEE. https://doi.org/10.1109/DEMPED. 2009.5292789
[82]. Usman, A., Joshi, B. M., & Rajpurohit, B. S. (2017, August). Review of fault modeling methods for permanent magnet synchronous motors and their th comparison. In 2017, IEEE 11 International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED) (pp. 141-146). IEEE. https://doi.org/ 10.1109/DEMPED.2017.8062347
[83]. Vaseghi, B., Nahid-Mobarakeh, B., Takorabet, N., & Meibody-Tabar, F. (2007, September). Modeling of nonsalient PM synchronous machines under stator winding interturn fault condition: Dynamic model-FEM model. In 2007, IEEE Vehicle Power and Propulsion Conference (pp. 635- 640). IEEE. https://doi.org/10.1109/VPPC.2007.4544200
[84]. Vaseghi, B., Takorabet, N., & Meibody-Tabar, F. (2009). Fault analysis and parameter identification of permanent-magnet motors by the finite-element method. IEEE Transactions on Magnetics, 45(9), 3290- 3295. https://doi.org/10.1109/TMAG.2009.2022156
[85]. Welchko, B. A., Jahns, T. M., & Hiti, S. (2002). IPM synchronous machine drive response to a single-phase open circuit fault. IEEE Transactions on Power Electronics, 17(5), 764-771. https://doi.org/10.1109/TPEL.2002.802180
[86]. Wen, L., Li, X., Gao, L., & Zhang, Y. (2017). A new convolutional neural network-based data-driven fault diagnosis method. IEEE Transactions on Industrial Electronics, 65(7), 5990-5998. https://doi.org/10.1109/TIE. 2017.2774777
[87]. Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2008). Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(2), 210-227. https://doi.org/10. 1109/TPAMI.2008.79
[88]. Yan, R., & Gao, R. X. (2006). Hilbert–Huang transform-based vibration signal analysis for machine health monitoring. IEEE Transactions on Instrumentation and Measurement, 55(6), 2320-2329. https://doi.org/10. 1109/TIM.2006.887042
[89]. Yang, B., Liu, R., & Chen, X. (2017). Fault diagnosis for a wind turbine generator bearing via sparse representation and shift-invariant K-SVD. IEEE Transactions on Industrial Informatics, 13(3), 1321-1331. https://doi. org/10.1109/TII.2017.2662215
[90]. Yang, J., Ye, H., & Zhou, W. (2014, August). A review of Permanent Magnet Synchronous Motor fault diagnosis. In 2014, IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific) (pp. 1-5). IEEE. https://doi.org/10.1109/ITEC-AP.2014.6940870
[91]. Yang, S., Li, W., & Wang, C. (2008, April). The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network. In 2008, International Conference on Condition Monitoring and Diagnosis (pp. 1327-1330). IEEE. https://doi.org/10.1109/CMD.2008.458 0221
[92]. Yassa, N., Rachek, M., Djerdir, A., & Becherif, M. (2016). Detecting of multi phase inter turn short circuit in the five permanent magnet synchronous motor. International Journal of Emerging Electric Power Systems, 17(5), 583-595. https://doi.org/10.1515/ijeeps-2016-0084
[93]. Yin, S., Ding, S. X., Xie, X., & Luo, H. (2014). A review on basic data-driven approaches for industrial process monitoring. IEEE Transactions on Industrial Electronics, 61(11), 6418-6428. https://doi.org/10.1109/TIE.2014.230 1773
[94]. Yong, C., Xu, Z., & Liu, X. (2017, October). Sensorless control at low speed based on HF signal injection and a new signal processing method. In 2017, Chinese Automation Congress (CAC) (pp. 3041-3045). IEEE. https://doi.org/10.1109/CAC.2017.8243297
[95]. Yu, S., & Tang, R. (2006). Electromagnetic and mechanical characterizations of noise and vibration in permanent magnet synchronous machines. IEEE Transactions on Magnetics, 42(4), 1335-1338. https://doi. org/10.1109/TMAG.2006.871637
[96]. Zafarani, M., Bostanci, E., Qi, Y., Goktas, T., & Akin, B. (2018). Interturn short-circuit faults in permanent magnet synchronous machines: An extended review and comprehensive analysis. IEEE Journal of Emerging and Selected Topics in Power Electronics, 6(4), 2173-2191. https://doi.org/10.1109/JESTPE.2018.2811538
[97]. Zhang, Z., Xu, Y., Yang, J., Li, X., & Zhang, D. (2015). A survey of sparse representation: Algorithms and applications. IEEE Access, 3, 490-530. https://doi.org/10. 1109/ACCESS.2015.2430359
[98]. Zheng, J., Wang, Z., Wang, D., Li, Y., & Li, M. (2017, July). Review of fault diagnosis of PMSM drive system in th electric vehicles. In 2017, 36 Chinese Control Conference (CCC) (pp. 7426-7432). IEEE. https://doi.org/ 10.23919/ChiCC.2017.8028529
[99]. Zhong, J., Yang, Z., & Wong, S. F. (2010, December). Machine condition monitoring and fault diagnosis based on support vector machine. In 2010, IEEE International Conference on Industrial Engineering and Engineering Management (pp. 2228-2233). IEEE. https://doi.org/10. 1109/IEEM.2010.5674594
[100]. Zhongming, Y. E., & Bin, W. U. (2000, August). A review on induction motor online fault diagnosis. In Proceedings IPEMC 2000. Third International Power Electronics and Motion Control Conference (IEEE Cat. No. 00EX435) (Vol. 3, pp. 1353-1358). IEEE. https://doi.org/ 10.1109/IPEMC.2000.883050
