TY - JOUR
T1 - A statistical model for predicting the liquid steel temperature in ladle and tundish by bootstrap filter
AU - Sonoda, Sho
AU - Murata, Noboru
AU - Hino, Hideitsu
AU - Kitada, Hiroshi
AU - Kano, Manabu
N1 - Funding Information:
GALEX is a NASA Small Explorer, launched in 2003 April. We gratefully acknowledge NASA’s support for construction, operation, and science analysis for the GALEX mission, developed in cooperation with the Centre National d’Etudes Spa-tiales of France and the Korean Ministry of Science and Technology. The VVDS is supported by the Centre National de la Recherche Scientifique of France and its Cosmology program, the Observatoire Astronomique Marseille Provence, and the Italian National Research Council.
PY - 2012
Y1 - 2012
N2 - A statistical model for predicting the liquid steel temperature in the ladle and in the tundish is developed. Given a large data set in a steelmaking process, the proposed model predicts the temperature in a seconds with a good accuracy. The data are divided into four phases at the mediation of five temperature measurements: before tapping from the converter (CV), after throwing ferroalloys into the ladle, before and after the Ruhrstahl-Heraeus (RH) processing, and after casting into the tundish in the continuous casting (CC) machine. Based on the general state space modeling, the bootstrap filter predicts the temperature phase by phase. The particle approximation technique enables to compute general-shaped probability distributions. The proposed model gives a prediction not as a point but as a probability distribution, or a predictive distribution. It evaluates both uncertainty of the prediction and ununiformity of the temperature. It is applicable to sensitivity analysis, process scheduling and temperature control.
AB - A statistical model for predicting the liquid steel temperature in the ladle and in the tundish is developed. Given a large data set in a steelmaking process, the proposed model predicts the temperature in a seconds with a good accuracy. The data are divided into four phases at the mediation of five temperature measurements: before tapping from the converter (CV), after throwing ferroalloys into the ladle, before and after the Ruhrstahl-Heraeus (RH) processing, and after casting into the tundish in the continuous casting (CC) machine. Based on the general state space modeling, the bootstrap filter predicts the temperature phase by phase. The particle approximation technique enables to compute general-shaped probability distributions. The proposed model gives a prediction not as a point but as a probability distribution, or a predictive distribution. It evaluates both uncertainty of the prediction and ununiformity of the temperature. It is applicable to sensitivity analysis, process scheduling and temperature control.
KW - Bootstrap filter
KW - General state space model
KW - Liquid steel temperature control
KW - Statistical modeling and simulation
KW - Steelmaking
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U2 - 10.2355/isijinternational.52.1086
DO - 10.2355/isijinternational.52.1086
M3 - Article
AN - SCOPUS:84863088966
VL - 52
SP - 1086
EP - 1091
JO - Transactions of the Iron and Steel Institute of Japan
JF - Transactions of the Iron and Steel Institute of Japan
SN - 0915-1559
IS - 6
ER -