Application of Artificial Intelligence Technologies for Diagnostics of Production Structures

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.

Automated summary

This paper discusses the issues and safety concerns related to the operation of torpedo ladle cars in metallurgical production. The authors have developed an algorithm based on neural networks to diagnose the lining state of ladle cars in the maritime industry, and proposed a distributed multi-agent information control system. The results show that the newly developed system has better performance in detecting burnout zones of the lining. Additionally, software has been developed to automate the assessment of the ladle car lining state and support decision-making in operation mode.