Dynamic model of liquid levels in the blast furnace hearth

Saxén, Henrik; Brännbacka, Johnny

doi:10.1111/j.1600-0692.2005.00728.x

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Electromotive force probes have been installed in BF-B to estimate variations in the liquid level of the hearth, and a strong correlation between the EMF measures and the iron level has been observed 17. The measurement of the EMF between two sensors that are welded to the furnace shell at two levels (one used as a common voltage reference) is a method to determine the amount of liquid in the hearth.…”

Section: Thermal State and Thermal Profile Analysismentioning

confidence: 99%

Monitoring and control of hearth refractory wear to improve blast furnace operation

Duarte¹,

Ruiz-Bustinza²,

Carrascal

et al. 2013

Ironmaking & Steelmaking

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Refractory wear and skull growth on the hearth walls and the bottom of the blast furnace have been researched. A series of thermocouples were installed in the hearth, and the temperature measurements were recorded in a structured query language every minute. A heat transfer model was used to study the temperature evolution and hearth wear profile using a commercial software package (MATLAB version 5.0) based on computational fluid dynamics. The location of the 1150uC isotherm in the hearth lining has been calculated. An online monitoring tool was used to analyse the temperature distribution in the hearth and offers, to the plant operators, periodic information on the refractory state. Electromotive force (EMF) probes were installed in the hearth to estimate the variations in the liquid level in the hearth and to determine the thermal state (TS) evolution. Good correlation is seen between EMF and TS, and the EMF amplitudes in the different tapholes follow and even precede the local TS.

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Section: Thermal State and Thermal Profile Analysismentioning

confidence: 99%

Monitoring and control of hearth refractory wear to improve blast furnace operation

Duarte¹,

Ruiz-Bustinza²,

Carrascal

et al. 2013

Ironmaking & Steelmaking

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“…Several studies in the literature have presented models of hearth drainage [1,2,[10][11][12][13]. A recent study by the present authors proposed a simple offline model simulating the liquid level fluctuations in a hearth with intermittent tapping [14].…”

Section: Introductionmentioning

confidence: 99%

Principal Component Analysis of Blast Furnace Drainage Patterns

2019

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Monitoring and control of the blast furnace hearth is critical to achieve the required production levels and adequate process operation, as well as to extend the campaign length. Because of the complexity of the draining, the outflows of iron and slag may progress in different ways during tapping in large blast furnaces. To categorize the hearth draining behavior, principal component analysis (PCA) was applied to two extensive sets of process data from an operating blast furnace with three tapholes in order to develop an interpretation of the outflow patterns. Representing the complex outflow patterns in low dimensions made it possible to study and illustrate the time evolution of the drainage, as well as to detect similarities and differences in the performance of the tapholes. The model was used to explain the observations of other variables and factors that are known to be affected by, or affect, the state of the hearth, such as stoppages, liquid levels, and tap duration.

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“…Methods for estimating other variables relating to the BF environment have been reported by several investigators. [4][5][6][7][8][9][10][11] However, to date, there have been no investigations of the state of the stockline by means of radar measurements.…”

Section: Introductionmentioning

confidence: 99%

Blast furnace stockline measurement using radar

Wei

Chen

Kelly

et al. 2014

Ironmaking & Steelmaking

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This paper presents a synergistic approach to stockline depth tracking within a blast furnace. Frequency modulated continuous wave (FMCW) radar can be used to measure the depth and surface profile of the burden surface; however, the radar signal is easily disturbed by radar anomalies during the process of continuous measurement. Data from the rotating chute and the charging signal provide information on the contextual relevance of these anomalies. An improved Kalman filter and anomaly detection model were developed to increase measurement accuracy by utilising contextual information. The approach was validated on production blast furnaces. The root mean squared (RMS) error in the measured depth was reduced by 17% when the proposed approach is used. The results suggest that this approach successfully adapts to changes in the pattern and characteristics of the burden surface.

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Dynamic model of liquid levels in the blast furnace hearth

Cited by 8 publications

References 10 publications

Monitoring and control of hearth refractory wear to improve blast furnace operation

Monitoring and control of hearth refractory wear to improve blast furnace operation

Principal Component Analysis of Blast Furnace Drainage Patterns

Blast furnace stockline measurement using radar

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