ISSN 2594-5327
75° Congresso Anual da ABM — vol. 75, num.75 (2022)
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IN THE PRESENT WORK, THE DEVELOPMENT OF AN ANOMALY DETECTION METHODOLOGY OF THE STRAND GUIDE OF A CONTINUOUS CASTING MACHINE BASED ON THE MONITORING OF THE STRAND EXTRACTION FORCE IS SHOWN. THE ANOMALY DETECTION IS BASED ON THE COMPARISON OF THE ACTUAL TOTAL DRIVE FORCE WITH THE NOMINAL VALUE, CALCULATED BY AN ARTIFICIAL NEURAL NETWORK (ANN), WHICH WAS TRAINED AND OPTIMIZED USING THE MOST RELEVANT CASTING PARAMETERS OF ACTUAL PRODUCTION DATA. THIS PAPER GIVES AN OVERVIEW ABOUT THE DEVELOPMENT PROCESS, THE GENERAL BEHAVIOR OF THE TOTAL EXTRACTION FORCE AND THE PRACTICAL APPLICATION OF THE SYSTEM IN PREVENTIVE CASTER MAINTENANCE.
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Continuous slab casting, Anomaly detection, strand withdrawal force, Machine learning
Continuous slab casting, Anomaly detection, strand withdrawal force, Machine learning
Como citar
Ramstorfer, Franz;
Sato, Gabriel Yoshiharu;
Demuner, Leonardo Martins.
DETECTION OF PROCESS- AND MACHINE ANOMALIES IN CONTINUOUS CASTING BY MONITORING THE STRAND WITHDRAWAL FORCE USING MACHINE LEARNING
,
p. 1320-1330.
In: 75° Congresso Anual da ABM,
São Paulo,
2022.
ISSN: 2594-5327
, DOI 10.5151/2594-5327-34813