Open AccessControl of the process of wear of the tribosystems based on the optical density of the lubricating oil using neural network models
Author(s) -
В. Г. Шрам,
Е. Д. Агафонов,
N. F. Orlovskaya,
G. V. Vashchenko,
А. В. Егоров
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1515/5/052045
Subject(s) - process (computing) , artificial neural network , optical density , petroleum engineering , process engineering , oil analysis , materials science , computer science , environmental science , artificial intelligence , engineering , optics , physics , operating system
The article considers the task of studying how the two processes relate - the destruction of lubricating oil and the wear of the elements of the tribosystem. The paper analyzes one of these indicators - the optical density of the oil, which characterizes the process of its destruction. The study includes the stage of constructing multifactor intelligent critical wear models depending on the optical density of the oil and the effort in the friction pair. The initial data for the construction of models are the results of measurements of the optical density of oils and the diameter of the wear spot. The obtained forecast models are indispensable for explaining the fundamental processes of wear that occur during the operation of lubricating oil. In addition to this, it should be noted that the results obtained make it possible to take the next step towards the creation of a new technique for the rapid assessment of the state of lubricating oil and the corresponding nature of the process of wear of the tribosystem.