학술논문

Predicting changes in the state of an industrial facility using machine learning methods.
Document Type
Article
Source
AIP Conference Proceedings. 2021, Vol. 2402 Issue 1, p1-5. 5p.
Subject
*MACHINE learning
*ACOUSTIC emission
Language
ISSN
0094-243X
Abstract
The purpose of this work is to predict the destruction of reinforced concrete beams that are subjected to three- point physical loads. A decrease in the number of acoustic emission signals with increasing load was taken as a criterion for the onset of destruction. Polynomial regression is considered as a forecasting method. Using the Sklearn Python library, the coefficients of the polynomial are fitted. The degree of the polynomial is found empirically. The developed method has shown good results in two practical experiments. [ABSTRACT FROM AUTHOR]