• DocumentCode
    606093
  • Title

    Fault diagnosis of induction motor using Motor Current Signature Analysis

  • Author

    Krishna, Merugu Siva Rama ; Ravi, Kiran S

  • Author_Institution
    Electrical Department, Rajiv Gandhi University of Knowledge Technologies, IIIT Nuzvid, Andhra Pradesh, India
  • fYear
    2013
  • fDate
    20-21 March 2013
  • Firstpage
    180
  • Lastpage
    186
  • Abstract
    Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical machines. Computer simulation of electric motor operation is particularly useful gaining an insight into their dynamic behavior and electro-mechanical interaction. A suitable model enables motor faults to be simulated and the change in corresponding parameters to be predicted without physical experimentation. This paper deals with a global method enabling the simulation of the squirrel cage induction machines under rotor and stator faults. This method is based on the coupled magnetic circuit theory. All self and mutual inductances of the circuit can be calculated using winding function theory. The proposed model is used to simulate the transient and steady state analysis of a healthy motor and a motor under stator, rotor, and mixed faults. This model gives the current spectrum analysis which is useful for diagnosis of stator and rotor faults using Motor Current Signature Analysis (MCSA) which is a non-invasive fault diagnosis technique [1].
  • Keywords
    Computational modeling; Computers; Equations; Loading; Mathematical model; Predictive models; Windings; Coupled Circuit Modelling; Fast Fourier Transform (FFT); Induction motor; Motor Current Signature Analysis (MCSA); Winding Function Theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits, Power and Computing Technologies (ICCPCT), 2013 International Conference on
  • Conference_Location
    Nagercoil
  • Print_ISBN
    978-1-4673-4921-5
  • Type

    conf

  • DOI
    10.1109/ICCPCT.2013.6528849
  • Filename
    6528849