ISSN 2594-5327
75th ABM Annual Congress - International — Vol. 75, Num. 75 (2022)
Title
DOI
Downloads
Abstract
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.
Keywords
Continuous slab casting, Anomaly detection, strand withdrawal force, Machine learning
Continuous slab casting, Anomaly detection, strand withdrawal force, Machine learning
How to cite
Ramstorfer, Franz; Demuner, Leonardo Martins; Sato, Gabriel Yoshiharu.
DETECTION OF PROCESS- AND MACHINE ANOMALIES IN CONTINUOUS CASTING BY MONITORING THE STRAND WITHDRAWAL FORCE USING MACHINE LEARNING,
p. 1320-1330.
In: 75th ABM Annual Congress - International,
São Paulo,
2022.
ISSN: 2594-5327, DOI 10.5151/2594-5327-34813