Early Diagnosis of Induction Machine Stator Winding Faults by Discrete Wavelet Transform

References

[1] da Costa C, Kashiwagi M, Mathias MH. Rotor failure detection of induction motors by wavelet transform and fourier transform in non-stationary condition. Case Stud Mech Syst Sig Process. 2015;1:15–26.10.1016/j.csmssp.2015.05.001Suche in Google Scholar

[2] Imoru O, Mokate L, Jimoh AA, Hamam Y. Diagnosis of rotor inter-turn fault of electrical machine at speed using stray flux test method. In: AFRICON. 2015;2015:1–5.Suche in Google Scholar

[3] Mahato S, Sharma M, Singh S. Steady-state and dynamic behavior of a single-phase self-excited induction generator using a three-phase machine. Int J Emerg Electr Power Syst. 2007;8.10.2202/1553-779X.1495Suche in Google Scholar

[4] Bayindir R, Bektas A. Fault detection and protection of induction motors using sensors. IEEE Trans Energy Conv. 2008;23:734–741.10.1109/TEC.2008.921558Suche in Google Scholar

[5] Siddiqui KM, Sahay K, Giri VK. Early; diagnosis of stator inter-turn fault in inverter driven induction motor by wavelet transform. IEEE 1st international conference on power electronics, intelligent control and energy systems (ICPEICES). 2016;1–6 2016.10.1109/ICPEICES.2016.7853647Suche in Google Scholar

[6] Bellini A, Filippetti F, Tassoni C, Capolino GA. Advances in diagnostic techniques for induction machines. IEEE Trans Ind Electron. 2008;55:4109–4126.10.1109/TIE.2008.2007527Suche in Google Scholar

[7] Filippetti F, Franceschini G, Tassoni C, Vas P. Recent developments of induction motor drives fault diagnosis using ai techniques. IEEE Trans Ind Electrons. 2000;47:994–1004.10.1109/41.873207Suche in Google Scholar

[8] Imoru O, Bhaskar MA, Jimoh A-G Hamam Y. Diagnosis of stator shorted-turn faults in induction machines using discrete wavelet transform. Afr J Sci Technol Innov Dev. 2017;9(3):349–355.10.1080/20421338.2017.1327933Suche in Google Scholar

[9] Toliyat HA, Nandi S, Choi S, Meshgin-Kel H. Electric machines: Modeling, condition monitoring, and fault diagnosis. CRC Press 2013.10.1201/b13008Suche in Google Scholar

[10] Auger F, Flandrin P. Improving the readability of time-frequency and time-scale representations by the reassignment method. IEEE Trans Sig Process. 1995;43:1068–1089.10.1109/78.382394Suche in Google Scholar

[11] Boashash B. Time-frequency signal analysis and processing: a comprehensive reference. Academic Press 2015.Suche in Google Scholar

[12] Peng ZK, Chu FL. Application of the wavelet transform in machine condition monitoring and fault diagnostics: A review with bibliography. Mech Syst Sig Process. 2004;18:199–221.10.1016/S0888-3270(03)00075-XSuche in Google Scholar

[13] Bessam B, Menacer A, Boumehraz M, Cherif H. Wavelet transform and neural network techniques for inter-turn short circuit diagnosis and location in induction motor. Int J Syst Assur Eng Manage 2015.10.1007/s13198-015-0400-4Suche in Google Scholar

[14] He Q. Vibration signal classification by wavelet packet energy flow manifold learning. J Sound Vib. 2013;332:1881–1894.10.1016/j.jsv.2012.11.006Suche in Google Scholar

[15] Shao R, Hu W, Wang Y, Qi X. The fault feature extraction and classification of gear using principal component analysis and kernel principal component analysis based on the wavelet packet transform. Measurement. 2014;54:118–132.10.1016/j.measurement.2014.04.016Suche in Google Scholar

[16] Bin GF, Gao JJ, Li XJ, Dhillon BS. Early fault diagnosis of rotating machinery based on wavelet packets–empirical mode decomposition feature extraction and neural network. Mech Syst Sig Process. 2012;27:696–711.10.1016/j.ymssp.2011.08.002Suche in Google Scholar

[17] Khan MA, Rahman MA. Discrete wavelet transform based detection of disturbances in induction motors. International Conference on Electrical and Computer Engineering 2006:462–465. 2006.10.1109/ICECE.2006.355669Suche in Google Scholar

[18] Antonino-Daviu J, Riera-Guasp M, Pineda-Snchez M, Pons-Llinares J, Puche-Panadero R, Perez-Cruz J. Feature extraction for the prognosis of electromechanical faults in electrical machines through the dwt. Int J Comput Intell Syst. 2009;2:158–167.10.1080/18756891.2009.9727651Suche in Google Scholar

[19] He Z. Wavelet analysis and transient signal processing applications for power systems. John Wiley & Sons 2016.10.1002/9781118977019Suche in Google Scholar

[20] Haves P, Khalsa S. study on energy sciences in buildings, efficiency and sustainability. In: Laboratory Berkeley National, editor(s). Model-based performance monitoring: Review of diagnostic methods and chiller case study. Lawrence. summer 2000:589–595. In: ACEEE2000.Suche in Google Scholar

[21] Zhong S, Wang F, Zhong S. Electrical, information engineering and mechatronics. Proceedings of the 2011 international conference on electrical, information engineering and mechatronics (EIEM 2011), lecture notes in electrical engineering 138, volume 1. London: Springer-Verlag, 1st ed. 2011:2012.10.1007/978-1-4471-2467-2Suche in Google Scholar

[22] Thomson WT, Fenger M. Current signature analysis to detect induction motor faults. IEEE Ind Appl Mag. 2001;7:26–34.10.1109/2943.930988Suche in Google Scholar

[23] Karmakar S, Chattopadhyay S, Mitra M, Sengupta S. Induction motor and faults. Singapore: Springer Singapor. 2016:7–28. http://dx.doi.org /10.1007/978-981-10-0624-1\_2.10.1007/978-981-10-0624-1_2Suche in Google Scholar

[24] Bonnett AH, Soukup GC. Cause and analysis of stator and rotor failures in three-phase squirrel-cage induction motors. IEEE Trans Ind Appl. 1992;28:921–937.10.1109/28.148460Suche in Google Scholar

[25] Küçüker A, Bayrak M. Detection of stator winding fault in induction motor using instantaneous power signature analysis. Turkish Journal of Electrical Engineering & Computer Sciences. 2015;23:1263–1271.10.3906/elk-1304-72Suche in Google Scholar

[26] Gritli Y, Rossi C, Zarri L, Filippetti F, Chatti A, Casadei D, Stefani A. Advanced diagnosis of broken bar fault in induction machines by using discrete wavelet transform under time-varying condition. IEEE international electric machines & drives conference (IEMDC). 2011:424–429. 2011.10.1109/IEMDC.2011.5994632Suche in Google Scholar

[27] Mallat SG. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans Pattern Anal Mach Intell. 1989;11:674–693.10.1109/34.192463Suche in Google Scholar

[28] Antonino-Daviu JA, Riera-Guasp M, Folch JR, Palomares MP. Validation of a new method for the diagnosis of rotor bar failures via wavelet transform in industrial induction machines. IEEE Trans Ind Appl. 2006;42:990–996.10.1109/TIA.2006.876082Suche in Google Scholar

[29] Miceli R, Gritli Y, Tommaso AD, Filippetti F, Rossi C. Vibration signature analysis for monitoring rotor broken bar in double squirrel cage induction motors based on wavelet analysis. COMPEL Int J Comput Math Electr Electron Eng. 2014;33:1625–1641.10.1108/COMPEL-09-2013-0304Suche in Google Scholar

[30] Dash RN, Subudhi B, Das S. Induction motor stator inter-turn fault detection using wavelet transform technique. 5th international conference on industrial and information systems 2010:436–441.Suche in Google Scholar

[31] Alehosseini A, Maryam AH, Mokhtari G, Gevork BG, Mohammadi M. Detection and classification of transformer winding mechanical faults using uwb sensors and bayesian classifier. Int J Emerg Electr Power Syst. 2015;16:207.10.1515/ijeeps-2014-0179Suche in Google Scholar

[32] Yahia K, Cardoso AJM, Ghoggal A, Zouzou S-E. Induction motors broken rotor bars diagnosis through the discrete wavelet transform of the instantaneous reactive power signal under time-varying load conditions. Electric Power Compon Syst. 2014;42:682–692.10.1080/15325008.2014.890966Suche in Google Scholar

[33] Sarkar TK, Su C, Adve R, Salazar-Palma M, Garcia-Castillo L, Boix RR. A tutorial on wavelets from an electrical engineering perspective. i. discrete wavelet techniques. IEEE Antennas Propag Mag. 1998;40:49–68.10.1109/74.735965Suche in Google Scholar