• DocumentCode
    151074
  • Title

    Automatizing the broken bar detection process via short time Fourier transform and two-dimensional piecewise aggregate approximation representation

  • Author

    Georgoulas, George ; Karvelis, Petros ; Stylios, Chrysostomos D. ; Tsoumas, I.P. ; Antonino-Daviu, J.A. ; Climente-Alarcon, Vicente

  • Author_Institution
    Dept. of Comput. Eng., Lab. of Knowledge & Intell. Comput., Artas, Greece
  • fYear
    2014
  • fDate
    14-18 Sept. 2014
  • Firstpage
    3104
  • Lastpage
    3110
  • Abstract
    This work presents an automated approach for detecting broken rotor bars in induction machines using the stator current during startup operation. The currents are analyzed using the well-known Short Time Fourier Transform (STFT) producing a two-dimensional time-frequency representation. This representation contains information regarding the presence of a characteristic transient component but requires further processing before it can be fed into a standard classification algorithm. In this work, this part is performed using the two dimensional extension of Piecewise Aggregate Approximation (PAA) that can deal with the two dimensional representation of STFT. The results (with both simulated and experimental data) suggest that the method can be used for the automatic detection of broken bars and even for determining the fault severity. Moreover, its low computational burden makes it ideal for its future use in online, unsupervised systems, as well as in portable condition monitoring devices.
  • Keywords
    Fourier transforms; approximation theory; asynchronous machines; rotors; time-frequency analysis; PAA; STFT; broken bar detection process; induction machines; short time Fourier transform; stator current; two-dimensional piecewise aggregate approximation representation; two-dimensional time-frequency representation; Bars; Circuit faults; Rotors; Spectrogram; Stators; Time-frequency analysis; Transient analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Conversion Congress and Exposition (ECCE), 2014 IEEE
  • Conference_Location
    Pittsburgh, PA
  • Type

    conf

  • DOI
    10.1109/ECCE.2014.6953822
  • Filename
    6953822