MODELING OF THE VIBRODIAGNOSTICS PROCESS OF VEHICLE GEARBOX BEARINGS BASED ON NEURAL NETWORKS
Authors:
1.
Nizhny Novgorod State Technical University named after R.E. Alexeyev
Nizhny Novgorod, Nizhny Novgorod, Russian Federation
Nizhny Novgorod, Nizhny Novgorod, Russian Federation
2.
Nizhny Novgorod State Technical University named after R.E. Alexeyev
Nizhny Novgorod, Nizhny Novgorod, Russian Federation
Nizhny Novgorod, Nizhny Novgorod, Russian Federation
3.
Nizhniy Novgorod State Technical University named after R.E. Alexeev
Type:
Сonference article
Pages:
from 229
to 234
Published:
23.07.2026
Subject area:
UDC 004.89
UDC 629
UDC 656.025.4
UDC 629
UDC 656.025.4
Language:
Russian
Keywords:
vibration diagnostics, wear, spectrum envelope characteristics, loading modes, neural networks
Abstract:
As an example of building and using an adaptive fuzzy inference system, we will consider the process of developing a neural network model to solve the problem of predicting deviations from the operational technical condition of vehicle gearboxes based on vibration characteristics.
As an example of building and using an adaptive fuzzy inference system, we will consider the process of developing a neural network model to solve the problem of predicting deviations from the operational technical condition of vehicle gearboxes based on vibration characteristics.
Keywords:
vibration diagnostics, wear, spectrum envelope characteristics, loading modes, neural networks
vibration diagnostics, wear, spectrum envelope characteristics, loading modes, neural networks
1. Minaev, Yu.N. Metody i algoritmy resheniya zadach identifikacii i prognozirovaniya v usloviyah neopredelennosti v neyrosetevom logicheskom bazise // Yu.N. Minaev [i dr.]. - M.: Goryachaya liniya – Telekom, 2003. - 342 s.
2. Rutkovskaya, D.L. Neyronnye seti, geneticheskie algoritmy i nechetkie sistemy // D.L. Rutkovskaya [i dr.]. - M.: Goryachaya liniya – Telekom, 2004. – 436 s.
3. Yarushkina, N.G. Osnovy teorii nechetkih i gibridnyh sistem / N.G. Yarushkina. - M.: Finansy i statistika, 2004. – 298 s.
