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Testing the Determinant of the Innovation Covariance Matrix Applied to Aircraft Sensor and Actuator/Surface Fault Detection

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Abstract

A new statistical fault detection technique based on the Kalman filter innovation covariance testing is proposed. The generalized variance (determinant) of the random Wishart matrix is used for this purpose as a fault detection statistic, and the testing problem is reduced to the determination of the asymptotes for Wishart determinants. In the simulations, the flight dynamics model of the F-16 fighter is investigated, and detection of sensor and actuator/surface failures, which affect the innovation covariance, is examined.

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Author information

Authors and Affiliations

  1. Faculty of Aeronautics and Astronautics, Istanbul Technical University, Maslak, Istanbul, 34469, Turkey

    Chingiz Hajiyev

  2. Faculty of Engineering, Halic University, Istanbul, Turkey

    Ulviye Hacizade

Authors
  1. Chingiz Hajiyev
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  2. Ulviye Hacizade
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Corresponding author

Correspondence to Chingiz Hajiyev .

Editor information

Editors and Affiliations

  1. Department of Airframe and Powerplant Maintenance, Anadolu University, Faculty of Aeronautics and Astronautics, Eskisehir, Turkey

    Tahir Hikmet Karakoç

  2. Department of Mechanical Engineering, Dokuz Eylul University, Faculty of Engineering, Buca, Izmir, Turkey

    C. Ozgur Colpan

  3. Department of Airframe and Powerplant Maintenance, Süleyman Demirel University, School of Civil Aviation, Isparta, Turkey

    Yasin Şöhret

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Hajiyev, C., Hacizade, U. (2018). Testing the Determinant of the Innovation Covariance Matrix Applied to Aircraft Sensor and Actuator/Surface Fault Detection. In: Karakoç, T., Colpan, C., Şöhret, Y. (eds) Advances in Sustainable Aviation. Springer, Cham. https://doi.org/10.1007/978-3-319-67134-5_19

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  • DOI: https://doi.org/10.1007/978-3-319-67134-5_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67133-8

  • Online ISBN: 978-3-319-67134-5

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