• DocumentCode
    2664958
  • Title

    Decision rules analysis for induction motor fault diagnosis based on rough set theory

  • Author

    Yueling, Zhao ; Yingli, Wang

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Liaoning Univ. of Technol., Jinzhou
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    93
  • Lastpage
    96
  • Abstract
    In order to extract simple and effective diagnostic rules from inconsistent diagnostic information, the method of fault diagnosis based on rough set theory is proposed. The efficiency of diagnostic rules is improved by pruning rules with certainty factor and introducing the coverage factor of decision rules to remove redundant information effectively. The availability of this method is proved by a fault diagnosis example of induction motor.
  • Keywords
    fault diagnosis; induction motors; rough set theory; decision rules analysis; diagnostic rule; fault diagnosis; induction motor; pruning rule; rough set theory; Data mining; Educational institutions; Fault diagnosis; Induction motors; Information analysis; Information science; Information systems; Petrochemicals; Set theory; Certainty Factor; Coverage Factor; Decision rules; Fault Diagnosis; Rough Set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2008. CCC 2008. 27th Chinese
  • Conference_Location
    Kunming
  • Print_ISBN
    978-7-900719-70-6
  • Electronic_ISBN
    978-7-900719-70-6
  • Type

    conf

  • DOI
    10.1109/CHICC.2008.4605450
  • Filename
    4605450
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2664958