• DocumentCode
    383065
  • Title

    Stator winding turn-fault detection for closed-loop induction motor drives

  • Author

    Tallam, Rangarajan M. ; Habetler, Thomas G. ; Harley, Ronald G.

  • Author_Institution
    Adv. Technol. Labs., Rockwell Autom., Milwaukee, WI, USA
  • Volume
    3
  • fYear
    2002
  • fDate
    13-18 Oct. 2002
  • Firstpage
    1553
  • Abstract
    Sensorless diagnostics for line-connected machines is based on extracting fault signatures from the spectrum of the line currents. However, for closed-loop drives, the power supply is a regulated current source and hence, the motor voltages must also be monitored for fault information. In this paper, a previously proposed neural network scheme for turn fault detection in line-connected induction machines is extended to inverter-fed machines, with special emphasis on closed-loop drives. Experimental results are provided to illustrate that the method is impervious to machine and instrumentation nonidealities, and that it requires lesser data memory and computation requirements than existing schemes, which are based on data look-up tables.
  • Keywords
    electric machine analysis computing; fault diagnosis; induction motor drives; invertors; neural nets; signal processing; spectral analysis; stators; 19 A; 230 V; 7.5 hp; AC drives; closed-loop drives; closed-loop induction motor drives; data look-up tables; data memory; fault information; fault signatures extraction; instrumentation nonidealities; inverter-fed machines; line currents spectrum; line-connected induction machines; motor voltages monitoring; neural network; power supply; regulated current source; sensorless diagnostics; stator winding turn-fault detection; turn fault detection; Data mining; Fault detection; Induction machines; Induction motor drives; Instruments; Monitoring; Neural networks; Power supplies; Stator windings; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Conference, 2002. 37th IAS Annual Meeting. Conference Record of the
  • Conference_Location
    Pittsburgh, PA, USA
  • ISSN
    0197-2618
  • Print_ISBN
    0-7803-7420-7
  • Type

    conf

  • DOI
    10.1109/IAS.2002.1043741
  • Filename
    1043741