• DocumentCode
    1945095
  • Title

    Immune Systems Inspired Approach to Anomaly Detection and Fault Diagnosis for Engines

  • Author

    Djurdjanovic, Dragan ; Liu, Jianbo ; Marko, Kenneth A. ; Ni, Jun

  • Author_Institution
    Univ. of Michigan, Ann Arbor
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    1375
  • Lastpage
    1382
  • Abstract
    As more electronic devices are integrated into automobiles to improve the reliability, drivability and maintainability, automotive diagnosis becomes increasingly difficult to deal with. Unavoidable design defects, quality variations in the production process as well as different usage patterns make it is infeasible to foresee all possible faults that may occur to the vehicle. As a result, many systems rely on limited diagnostic coverage provided by a diagnostic strategy which tests only for a priori known or anticipated failures, and presumes the system is operating normally if the full set of tests is passed. To circumvent these difficulties and provide a more complete coverage for detection of any fault, a new paradigm for design of automotive diagnostic systems is needed. An approach inspired by the functionalities and characteristics of natural immune system is presented and discussed in the paper. The feasibility of the newly proposed paradigm is also partially demonstrated through application examples.
  • Keywords
    automotive components; automotive electronics; fault diagnosis; internal combustion engines; anomaly detection; automobiles; automotive diagnosis; diagnostic strategy; engines; fault diagnosis; immune systems inspired approach; Automobiles; Automotive engineering; Engines; Fault detection; Fault diagnosis; Immune system; Maintenance; Production; System testing; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4371159
  • Filename
    4371159