• DocumentCode
    2139090
  • Title

    A comparison of spectrum estimation techniques for sensorless speed detection in induction machines

  • Author

    Hurst, K.D. ; Habetler, T.G.

  • Author_Institution
    Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    1
  • fYear
    1995
  • fDate
    8-12 Oct 1995
  • Firstpage
    553
  • Abstract
    This paper compares digital spectrum estimation techniques which can be used to extract speed information from rotor slot and eccentricity harmonics contained in the stator current. In previous work, the speed-related current harmonics have been shown to improve the performance of existing back EMF-based sensorless schemes, since they are parameter-independent and exist at virtually any nonzero speed. Digital filtering, however, requires a minimum data sampling time in order to achieve the desired resolution. The contribution of this paper is to determine the optimal method for accurately extracting the speed-related harmonics in the least amount of time. Several digital signal processing algorithms are investigated, including the fast Fourier transform and other traditional methods, as well as parametric techniques such as linear predictions. Each approach is evaluated on the criteria of accuracy, robustness and computation time given a short data record
  • Keywords
    asynchronous machines; fast Fourier transforms; filtering theory; harmonics; machine theory; parameter estimation; rotors; signal processing; stators; velocity; accuracy; computation time; current harmonics; digital filtering; digital signal processing algorithms; digital techniques; eccentricity harmonics; fast Fourier transform; induction machines; linear predictions; minimum data sampling time; parametric techniques; performance; resolution; robustness; rotor slot harmonics; sensorless speed detection; spectrum estimation techniques; speed-related harmonics; stator current; Data mining; Digital filters; Digital signal processing; Filtering; Power harmonic filters; Signal processing algorithms; Signal resolution; Signal sampling; Spectral analysis; Stators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industry Applications Conference, 1995. Thirtieth IAS Annual Meeting, IAS '95., Conference Record of the 1995 IEEE
  • Conference_Location
    Orlando, FL
  • ISSN
    0197-2618
  • Print_ISBN
    0-7803-3008-0
  • Type

    conf

  • DOI
    10.1109/IAS.1995.530348
  • Filename
    530348