On-line detection of stator winding faults in controlled induction machine drives

The operation of induction machines with fast switching power electric devices puts additional stress on the stator windings what leads to an increased probability of machine faults. These faults can cause considerable damage and repair costs and - if not detected in an early stage - may end up in a total destruction of the machine. To reduce maintenance and repair costs many methods have been developed and presented in literature for an early detection of machine faults. This paper gives an overview of todaypsilas detection techniques and divides them into three major groups according to their underlying methodology. The focus will be on methods which are applicable to todaypsilas inverter-fed machines. In that case and especially if operated under controlled mode, the behavior of the machine with respect to the fault is different than for grid supply. This behavior is discussed and suitable approaches for fault detection are presented. Which method is eventually to choose, will depend on the application and the available sensors as well as hard- and software resources, always considering that the additional effort for the fault detection algorithm has to be kept as low as possible. The applicability of the presented fault detection techniques are also confirmed with practical measurements.

[1]  Hamid A. Toliyat,et al.  Novel frequency domain based technique to detect incipient stator inter-turn faults in induction machines , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[2]  G. Joksimovic,et al.  The detection of interturn short circuits in the stator windings of operating motors , 1998, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200).

[3]  Humberto Henao,et al.  On the stray flux analysis for the detection of the three-phase induction machine faults , 2003, 38th IAS Annual Meeting on Conference Record of the Industry Applications Conference, 2003..

[4]  J. A. Haylock.  On-line detection of winding short-circuits in inverter fed drives , 1999, IEMDC 1999.

[5]  R. Maier,et al.  Protection of squirrel cage induction motor utilizing instantaneous power and phase information , 1990, Conference Record of the 1990 IEEE Industry Applications Society Annual Meeting.

[6]  Thomas M. Wolbank,et al.  On-line stator winding faults detection in inverter fed induction motors by stator current reconstruction , 1999, IEMDC 1999.

[7]  Peter J. Unsworth,et al.  Stator fault diagnosis in induction motors using power decomposition , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).

[8]  William James Premerlani,et al.  A new approach to on-line turn fault detection in AC motors , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[9]  A.J. Marques Cardoso,et al.  Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park's vector approach , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[10]  Mohamed El Hachemi Benbouzid.  A review of induction motors signature analysis as a medium for faults detection , 2000, IEEE Trans. Ind. Electron..

[11]  Christian Kral,et al.  Sequences of field-oriented control for the detection of faulty rotor bars in induction machines-the Vienna Monitoring Method , 1998, IEEE Trans. Ind. Electron..

[12]  T. G. Habetler,et al.  Insulation failure prediction in induction machines using line-neutral voltages , 1997, IAS '97. Conference Record of the 1997 IEEE Industry Applications Conference Thirty-Second IAS Annual Meeting.

[13]  M. Dalva,et al.  Condition monitoring methods, failure identification and analysis for high voltage motors in petrochemical industry , 1997 .

[14]  Birsen Yazici,et al.  Sensorless, online motor diagnostics , 1997 .