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.
Efficient fault diagnosis of helicopter gearboxes
World Congress International Federation of Automatic Control ; 1993 ; Sydney, Australia
1993-07-01
Aufsatz (Konferenz)
Keine Angabe
Englisch
Fuzzy connectionist network for fault diagnosis of helicopter gearboxes
Tema Archiv | 1995
|Unsupervised Connectionist Network for Fault Diagnosis of Helicopter Gearboxes
British Library Conference Proceedings | 1997
|Structure-Based Connectionist Network for Fault Diagnosis of Helicopter Gearboxes
Online Contents | 1998
|