Acoustic diagnostics of local damages of spur wheels in multi-shaft drive using neural network models


In the course of acoustic diagnosis of multi-shaft drives on the basis of spur wheels, the diagnostician is faced with the problem of excessive saturation of the analyzed signal with various kinds of frequency components. Reducing the amount of data analyzed may result in the loss of important diagnostic information. Therefore, in order to make the diagnostician’s work easier and at the same time maintain the accuracy of the diagnosed local damage to the gear tooth it is necessary to identify the list of informative frequency components. They should respond to the occurrence of this defect in the tooth-contact zone and have a sufficiently thoroughly studied mathematical framework that will make it possible to use methods of their automatic determination. The obtained digital image will allow using artificial neural network models for its processing.

About the authors

A. N. Parfiyevich

Brest State Technical University

Author for correspondence.


Senior Lecturer of the Department “Mechanical Engineering and Car Operation”

A. V. Dragan

Brest State Technical University



Candidate of Science (Engineering), Associate Professor,
Associate Professor of the Department “Mechanical Engineering and Car Operation”

V. A. Sokol

Brest State Technical University



Senior Lecturer of the Department “Mechanical Engineering and Car Operation”


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