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Above Burden Temperature Data Probes Interpretation to Prevent Malfunction of Blast Furnaces ‐ Part 1: Intelligent Information Preprocessing
Author(s) -
Martín D. R.,
Mochón J.,
Jiménez J.,
Verdeja L. F.,
Rusek P.,
Ayala N.
Publication year - 2009
Publication title -
steel research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.603
H-Index - 49
eISSN - 1869-344X
pISSN - 1611-3683
DOI - 10.2374/sri08sp046
Subject(s) - blast furnace , preprocessor , process (computing) , set (abstract data type) , data pre processing , data mining , computer science , engineering , artificial intelligence , materials science , metallurgy , programming language , operating system
In the last few years, the use of computers has made it possible to achieve a better image of blast furnace performance, allowing the establishment of models, the comparison of variables and the construction of powerful databases to store the variables and their evolution during the process. Nevertheless, part of the investment made in blast furnace equipment is not properly utilized and a considerable part of the information collected could be put to much better use. The application of modern data mining techniques has overcome these problems. This work shows ways to apply these techniques to data from probes located in the throat or shaft of the blast furnace, as well as how to extract useful information by defining and classifying a set of patterns in classes from temperature profiles that have been linked to the stability of the process in steelworks with blast furnaces.