A supplied heat quantity estimation method includes an estimation step of estimating a change in carried out sensible heat by in-furnace passing gas and a change in carried in sensible heat supplied by a raw material preheated by the in-furnace passing gas, and estimating a quantity of heat supplied to pig iron in a blast furnace in consideration of the estimated changes of the carried out sensible heat and the carried in sensible heat. The estimation step includes a step of estimating a quantity of heat supplied to pig iron in consideration of heat dissipated from the blast furnace during an air blowing break, and a step of estimating a quantity of heat held in deadman coke present in the blast furnace, and estimating the quantity of heat supplied to pig iron in consideration of the estimated quantity of heat held in deadman coke.

Controlling circumferential variability in a blast furnace may include generating a predictive model that sets up a relationship between a standard deviation of a selected state variable, state variables and one or more control variables in blast furnace operation for predicting the standard deviation. A number of circumferential sections of the blast furnace is defined, and the predictive model associated with the selected state variable for each of the circumferential sections is trained based on process data of the blast furnace. A plurality trained predictive models is generated associated with different circumferential sections and different selected state variables. One or more future control variable set points that minimize a sum of the plurality of predictive models, is determined. One or more future control variable set points is transmitted to a control system to control the blast furnace operation.

Controlling circumferential variability in a blast furnace may include generating a predictive model that sets up a relationship between a standard deviation of a selected state variable, state variables and one or more control variables in blast furnace operation for predicting the standard deviation. A number of circumferential sections of the blast furnace is defined, and the predictive model associated with the selected state variable for each of the circumferential sections is trained based on process data of the blast furnace. A plurality trained predictive models is generated associated with different circumferential sections and different selected state variables. One or more future control variable set points that minimize a sum of the plurality of predictive models, is determined. One or more future control variable set points is transmitted to a control system to control the blast furnace operation.

A supply heat amount estimating method for estimating an amount of heat supplied to pig iron in a blast furnace from an amount of heat supplied into the blast furnace and a rate of production of molten pig iron in the blast furnace, the supply heat amount estimating method includes: estimating a change in carried-out sensible heat by an in-furnace passing gas and a change in carried-in sensible heat supplied by a raw material preheated by the in-furnace passing gas and estimating the amount of heat supplied to the pig iron in the blast furnace in consideration of the estimated changes in the carried-out sensible heat and the carried-in sensible heat.

A hot metal temperature prediction method includes a reaction amount calculation step (S1) of calculating a reaction amount inside a blast furnace using a physical model that takes into account reactions and heat transfer phenomena inside the blast furnace, a deviation calculation step (S2) of calculating a deviation between the reaction amount calculated using the physical model and a measured reaction amount, a model parameter adjustment step (S3) of adjusting a parameter of the physical model that causes drift in a gas inside the blast furnace, so that the calculated deviation is reduced, and a hot metal temperature prediction step (S4) of predicting a future hot metal temperature using the physical model for which the parameter was adjusted.

A hot metal temperature prediction method includes a reaction amount calculation step (S1) of calculating a reaction amount inside a blast furnace using a physical model that takes into account reactions and heat transfer phenomena inside the blast furnace, a deviation calculation step (S2) of calculating a deviation between the reaction amount calculated using the physical model and a measured reaction amount, a model parameter adjustment step (S3) of adjusting a parameter of the physical model that causes drift in a gas inside the blast furnace, so that the calculated deviation is reduced, and a hot metal temperature prediction step (S4) of predicting a future hot metal temperature using the physical model for which the parameter was adjusted.

Disclosed is a system and method for evaluating a status of a refractory material in metallurgical vessels, including furnaces and ladles, wherein a slag buildup is formed on the surface of such material as a result of scrap accumulation and chemical reactions occurring during the melting of metals in such vessels. The system and method are operative to determine both a rate of degradation of the material under evaluation, including the thickness of such material, and a measure of the slag buildup to predict and extend the operational life and improve the maintenance plan of the vessel. The system is capable of determining the thickness of and the slag buildup on the entire material under evaluation by sampling a number of regions of such material with different types of sensors, characterizing the surface profile of such material, and using appropriate signal processing techniques and artificial intelligence algorithms.

Probes, blast furnaces equipped therewith, and methods of fabricating probes. Such a probe includes a base, a shell connected to the base and constructed of at least first and second housing members that extend together along a length of the probe in a longitudinal direction thereof, and at least one support structure interconnecting the first and second housing members. The probe includes a coolant circuit comprising at least one coolant passage within an interior cavity of the shell. The coolant passage has at least one tube supported by the support structure so that the tube contacts at least one of the first and second housing members. At least one sensor is disposed in the second housing member for performing a measurement at an exterior of the shell.

An apparatus includes: a guide portion in which a reflection plate is disposed in an opening portion at one end, and an antenna is disposed at the other end, and which is to be inserted into a blast furnace through an opening of the furnace; a guide portion moving unit which moves the guide portion to the inside or outside of the furnace; a guide portion rotating unit which rotates the guide portion; and a reflection plate tilting unit which changes a tilt angle of the reflection plate with respect to the antenna. During measurement, the opening portion of the guide portion is protruded into the furnace, and the guide portion rotating unit and the reflection plate tilting unit are driven to scan planarly or linearly the surface of a burden in the furnace.

An apparatus includes: a guide portion in which a reflection plate is disposed in an opening portion at one end, and an antenna is disposed at the other end, and which is to be inserted into a blast furnace through an opening of the furnace; a guide portion moving unit which moves the guide portion to the inside or outside of the furnace; a guide portion rotating unit which rotates the guide portion; and a reflection plate tilting unit which changes a tilt angle of the reflection plate with respect to the antenna. During measurement, the opening portion of the guide portion is protruded into the furnace, and the guide portion rotating unit and the reflection plate tilting unit are driven to scan planarly or linearly the surface of a burden in the furnace.