Helicopter Gearbox Fault Detection: A Neural Network Based Approach
Author:
- 1 July 1999
- journal article
- Published by ASME International in Journal of Vibration and Acoustics
- Vol. 121 (3) , 265-272
Abstract
One of the most dangerous problems that can occur in both military and civilian helicopters is the failure of the main gearbox. Currently, the principal method of controlling gearbox failure is to regularly overhaul the complete system. This paper considers the feasibility of using a neural network to perform fault detection on vibration measurements given by accelerometer data. The details and results obtained from studying the neural network approach are presented. Some of the elementary underlying physics will be discussed along with the preprocessing necessary for analysis. Several networks were investigated for detection and classification of the gearbox faults. The performance of each network will be presented. Finally, the network weights will be related back to the underlying physics of the problem.Keywords
This publication has 2 references indexed in Scilit:
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- A Signal Processing Technique for Detecting Local Defects in a Gear from the Signal Average of the VibrationProceedings of the Institution of Mechanical Engineers, Part C: Mechanical Engineering Science, 1985