Information System for Diagnosing the Condition of the Complex Structures Based on Neural Networks

In this paper, we describe the relevance of diagnosing the lining condition of steel ladles in metallurgical facilities. Accidents with steel ladles lead to losses and different types of damage in iron and steel works. We developed an algorithm for recognizing thermograms of steel ladles to identify...

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Bibliographic Details
Published inEnergies (Basel) Vol. 15; no. 9; p. 2977
Main Authors Emelianov, Vitalii, Chernyi, Sergei, Zinchenko, Anton, Emelianova, Nataliia, Zinchenko, Elena, Chernobai, Kirill
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.05.2022
Subjects
Algorithms
Automation
Burnout
diagnosing
information system
lining
Methods
Neighborhoods
neural network
Neural networks
software
steel ladle
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ISSN1996-1073
1996-1073
DOI10.3390/en15092977

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Summary:In this paper, we describe the relevance of diagnosing the lining condition of steel ladles in metallurgical facilities. Accidents with steel ladles lead to losses and different types of damage in iron and steel works. We developed an algorithm for recognizing thermograms of steel ladles to identify burnout zones in the lining based on the technology and design of neural networks. A diagnostic system structure for automated evaluating of the technical conditions of steel ladles without taking them out of service has been developed and described.
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ISSN:1996-1073
1996-1073
DOI:10.3390/en15092977