Application of Artificial Intelligence Technologies for Diagnostics of Production Structures

Abstract

The paper presents that during the operation of torpedo ladle cars in metallurgical production, problems periodically arise with ensuring the safety of their use. The authors have highlighted the relevance and necessity of the solution to the problem of diagnosing the lining state of ladle cars to ensure their safe functioning. To solve the problem of diagnosing the lining state of ladle cars for the maritime industry, an algorithm for detecting burnout zones of a lining based on a neural network has been developed. The authors propose and describe a distributed multi-agent information control system for the operation of torpedo ladle cars. The results for detecting burnout zones of a lining by the standard system and newly developed system are presented. To automate assessing the lining state of the ladle car and support in making decisions regarding operation mode of the ladle cars, the software has been developed.

Experimental Study Results Processing Method for the Marine Diesel Engines Vibration Activity Caused by the Cylinder-Piston Group Operations

“…One such randomized experimental tool is the random balance method, which has been successfully applied in various fields of research, including agriculture, medicine, and mechanical engineering [42,43]. The random balance method assumes a random distribution of procedures between experimental units while ensuring the balance of the scheme in relation to various factors that can affect the result [23,42]. Such balance helps minimize the influence of variables that can lead to biased estimates of influence effects [29,30].…”

A Deep Neural Network Method for Water Areas Extraction Using Remote Sensing Data

“…The use of this activation function allows to reduce computational costs due to the absence of complex mathematical operations, which will lead to a decrease in the training time of the model [24].…”