Application of a diagnostic system to a helicopter gearbox is presented. The diagnostic system is a nonparametric pattern classifier that uses a multi-valued influence matrix (MVIM) as its diagnostic model and benefits from a fast learning algorithm that enables it to estimate its diagnostic model from a small number of measurement-fault data. To test this diagnostic system, vibration measurements were collected from a helicopter gearbox test stand during accelerated fatigue tests and at various fault instances. The diagnostic results indicate that the MVIM system can accurately detect and diagnose various gearbox faults so long as they are included in training.


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    Titel :

    Efficient fault diagnosis of helicopter gearboxes


    Beteiligte:
    Chin, H. (Autor:in) / Danai, K. (Autor:in) / Lewicki, D. G. (Autor:in)

    Kongress:

    World Congress International Federation of Automatic Control ; 1993 ; Sydney, Australia


    Erscheinungsdatum :

    1993-07-01


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch


    Schlagwörter :


    Fuzzy connectionist network for fault diagnosis of helicopter gearboxes

    Jammu, V.B. / Danai, K. / Lewicki, D.G. | Tema Archiv | 1995


    Unsupervised Connectionist Network for Fault Diagnosis of Helicopter Gearboxes

    Jammu, V. / Danai, K. / Lewicki, D. et al. | British Library Conference Proceedings | 1997