Paper Info
Title
Soft-sensing method for slag-crust state of blast furnace based on two-dimensional decision fusion.
Abstract
Slag crusts on the cooling stave of a blast furnace offer greatly protection for the furnace wall. Frequent forming and shedding of slag crusts (FSSCs) cause severe erosion on the wall, which affects the life of a blast furnace. However, it is very difficult to detect the FSSCs directly because of restrictions imposed by the structure of a blast furnace and detecting costs. This paper presents a soft-sensing method based on two-dimensional decision fusion to detect the state of slag crust (SSC) of a blast furnace. First, a soft-sensing scheme for SSC is put forward on the basis of features of slag crusts and the temperature detected in cooling stave. Next, methods for calculating a temperature threshold (TT) and a change-rate threshold of temperature (CRTT) are presented according to the characteristics of slag crusts. Finally, a two-dimensional decision method is presented by fusing the TT and CRTT to determine the SSC of the blast furnace. The experiment results based on industrial data demonstrate the effectiveness of the method.
Year
DOI
Venue
2018
10.1016/j.neucom.2018.07.033
Neurocomputing
Keywords
Field
DocType
State of slag crust,Soft-sensing method,Two-dimensional decision fusion,Temperature threshold,Change-rate threshold of temperature
Slag,Decision fusion,Pattern recognition,Crust,Blast furnace,Artificial intelligence,Erosion,Soft sensing,Mathematics,Nuclear engineering
Journal
Volume
ISSN
Citations 
315
0925-2312
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Jianqi An191.47
Jialiang Zhang29411.46
Min Wu33582272.55
Jin-Hua She41841182.27
Takao Terano541399.61