Diagnosing the technical condition of planetary gearbox using the artificial neural network based on analysis of non-stationary signals
 
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AGH University of Science and Technology, Department of Mechanics and Vibroacoustics
CORRESPONDING AUTHOR
Paweł Pawlik   

AGH University of Science and Technology, Department of Mechanics and Vibroacoustics, al. A. Mickiewicza 30, 30-059 Cracow, Polska
Publication date: 2016-06-04
Submission date: 2016-04-04
Acceptance date: 2016-04-05
 
Diagnostyka 2016;17(2):57–64
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ABSTRACT
This paper deals with the problem of diagnosing the technical condition of a planetary gearbox operating at variable load. The severity of the subject and related difficulties were discussed. Theoretical basis of analysis of non-stationary signals (order analysis) and its use in signal resampling was also presented. The paper tests the functionality of the planetary gearbox diagnostics method. The Multilayer Perceptron Network was used to identify and classify the damage. The network’s learning vectors were built on the basis of order analysis results and measurements of the planetary gearbox load. The functionality of two-layer and three-layer unidirectional artificial neural network was also analysed for potential use in diagnosing the technical condition of planetary gears.
eISSN:2449-5220
ISSN:1641-6414