THE USE OF ARTIFICIAL NEURAL NETWORK MODELS IN THE ACOUSTIC DIAGNOSTICS OF MULTI-SHAFT GEAR DRIVES

Authors

  • Andrey Nikolaevich Parfievich Brest State Technical University
  • Victor Alexandrovich Sokol Brest State Technical University
  • Mikhail Vladimirovich Neroda Brest State Technical University

DOI:

https://doi.org/10.36773/1818-1112-2021-126-3-72-75

Keywords:

gear wheel, local defect, artificial neural network model, diagnostics, acoustic signal, multi-shaft gear drive

Abstract

The article considers the possibility of diagnosing a multi-shaft gear mechanical system based on the analysis of an acoustic signal using artificial neural network models on the example of the speed box of the SN-501 lathe. A sufficiently high efficiency and accuracy of detecting a local defect of the gear wheel in conditions of high acoustic activity of all components of the drive when monitoring its condition is shown.

Author Biographies

Andrey Nikolaevich Parfievich, Brest State Technical University

Master of Technical Sciences, Senior Lecturer of the Department of Mechanical Engineering and Operation of Vehicles, Research Engineer, Brest State Technical University, Brest, Belarus.

 

 

 

Victor Alexandrovich Sokol, Brest State Technical University

Master of Technical Sciences, Senior Lecturer of the Department of Mechanical Engineering and Operation of Vehicles, Brest State Technical University, Brest, Belarus.

 

 

 

Mikhail Vladimirovich Neroda, Brest State Technical University

The First Vice Rector, Ph.D in Engineering, Associate Professor, Brest State Technical University, Brest, Belarus.

 

 

 

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Published

2021-12-02

How to Cite

(1)
Parfievich, A. N.; Sokol, V. A.; Neroda, M. V. THE USE OF ARTIFICIAL NEURAL NETWORK MODELS IN THE ACOUSTIC DIAGNOSTICS OF MULTI-SHAFT GEAR DRIVES. Вестник БрГТУ 2021, 72-75.

Issue

No. 3(126) (2021): Vestnik of Brest State Technical University

Section

Mechanical Engineering

License

Copyright (c) 2021 Brest State Technical University

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