• DocumentCode
    554166
  • Title

    A Negative Selection Algorithm-based motor fault detection scheme

  • Author

    Gao, X.Z. ; Wang, Xiongfei ; Ovaska, S.J. ; Arkkio, Antero ; Zenger, Kai ; Xiaofeng Wang

  • Author_Institution
    Inf. Eng. Coll., Shanghai Maritime Univ., Shanghai, China
  • Volume
    3
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    1583
  • Lastpage
    1587
  • Abstract
    In this paper, we propose a Negative Selection Algorithm (NSA)-based motor fault detection system. Only the feature signals of the healthy motors are needed here for generating the NSA detectors. Different from the conventional fault detection approaches, no prior knowledge of the motor fault types is assumed to be known beforehand in the proposed scheme. Our motor fault detection method is examined using both the rotor and stator faults in computer simulations. We further explore its applicability in case of fault detection with varying motor loads.
  • Keywords
    artificial immune systems; electric machines; fault diagnosis; rotors; signal processing; stators; NSA detector; artificial immune system; electrical machine; healthy motor; motor fault detection; motor fault type; motor load; negative selection algorithm; rotor fault; signal; stator fault; Detectors; Educational institutions; Fault detection; Feature extraction; Immune system; Rotors; Stators; Artificial Immune Systems (AIS); Negative Selection Algorithm (NSA); electrical machines; fault detection; motors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2011 Seventh International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4244-9950-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2011.6022383
  • Filename
    6022383