A system and equipment to measure and control the feeding of load material into an electrical arc furnace (EAF) includes an automatic control device feeding the load material; a measuring device positioned between the EAF and the tilting platform that includes an upper plate adapted to slide against the EAF, a lower plate engaged to the tilting platform, and a ring structure therebetween having a peripheral ring wall, a ring plate extending across the ring structure, and a contact member coupled to the ring plate that upperly contacts the upper plate and lowerly approaches, without contacting the lower plate; and one or more sensors measuring a deformation of the ring plate upon application of a load on the upper plate.

At least one measurement value of a measurement variable characterizing the operating state of each of a plurality of system components that influence the operating conditions of an arc furnace is detected and compared to a respective currently permissible threshold value for the measurement variable. A maximum power that can be supplied to the arc furnace within a time window while satisfying all currently permissible threshold values is determined based on the result of the comparison.

A method for controlling a temperature of a molten steel during ladle furnace (LF) refining based on interpretable machine learning includes: acquiring process data of the LF refining and a target temperature of the molten steel during the LF refining; acquiring a prediction model for the temperature of the molten steel during the LF refining; calculating a base value for prediction of the temperature of the molten steel, SHapley Additive explanations (SHAP) values of key factor parameters, and a relationship trend between the key factor parameters and the SHAP values; and calculating a predicted value of the temperature of the molten steel during the LF refining, and acquiring a control result for the temperature of the molten steel during the LF refining according to the relationship trend and the predicted value of the temperature of the molten steel during the LF refining.

A method for predicting an impurity concentration of molten iron after refining of molten iron to be refined in an electric arc furnace facility includes inputting, into an impurity concentration prediction model, an amount of individual ferrous scrap material charged, the ferrous scrap material being classified by type, and at least one of the impurity concentration of molten iron in a preceding charge, an amount of residual molten iron in the preceding charge, and market transaction price information of an impurity; and outputting the impurity concentration of the molten iron in a subsequent charge.

Some implementations provide an integrated system that includes: a wastewater treatment system configured to process wastewater released by one or more furnaces at a steelmaking plant, and generates reused wastewater using the wastewater; a heat recovery apparatus configured to utilize exhaust gas from the one or more furnaces at the steelmaking plant, and heat the reused wastewater generated by the wastewater treatment system above a threshold temperature; and a generator configured to receive, through a water inlet, the reused wastewater heated above the threshold temperature; and an absorption system arranged in circulation with the generator, and wherein the reused water is supplied above a threshold amount such that the generator drives the absorption system and produces cooled air inside the steelmaking plant.

A converter slagging monitoring method and device. The method comprises: acquiring converter smelting data containing converter noise data and oxygen lance vibration data in real time; based on a pre-established slagging monitoring model, calculating the thickness of slags in a converter molten bath by virtue of the acquired converter smelting data; comparing the calculated thickness of slags with a splashing threshold value and a drying threshold value which are contained in the slagging monitoring model, judging whether a comparison result characterizes the occurrence of splashing or drying, and when the comparison result characterizes the occurrence of splashing or drying, acquiring corresponding splashing information or drying information; and finally, according to the splashing information or drying information, making a corresponding splashing control scheme or drying control scheme to guide a subsequent slagging operation so as to achieve the smooth control of the lance position.

A cold iron source melting ratio estimation device that estimates a melting ratio of a cold iron source charged into a converter-type refining furnace during refining of molten iron in the converter-type refining furnace. The device includes: an input section to which measured values of in-furnace information or estimated values of the in-furnace information is input, the in-furnace information including a molten iron temperature and a carbon concentration in the molten iron during refining; a database section that stores a model equation and parameters related to a refining reaction of the molten iron in the converter-type refining furnace; a computation section that computes the melting ratio of the cold iron source using the measured values or the estimated values input to the input section; and an output section that displays the melting ratio of the cold iron source computed by the computation section.

Disclosed is a control system for a melting process in an electric arc furnace for melting a metallic material that minimizes desired process properties such as the melting time or the total power consumption of the melting process. The system includes a processing unit adapted for receiving or collecting measured data of at least one process variable, determining the current state of the process, performing an optimization of the melting process, determining a process input based on the result of the optimization, and controlling the melting process with the process input. A method is also presented herein.

A furnace state estimation device (1) including: an input unit (11) configured to receive track record information and conditions of refining treatment; a model determination unit (14) configured to determine model parameters using past model parameters; a furnace state calculation unit (15) configured to calculate state quantities, including temperature and component concentration of molten metal and component concentration of slag, in a furnace, using the determined model parameters; and a model parameter calculation unit (13) configured to calculate model parameters in the refining treatment of the target charge, based on an evaluation function that includes terms representing a mass balance error and a heat balance error in the furnace from beginning to end of a particular period of time in the refining treatment, using track record information including results of the refining treatment of the target charge.

A method and system for predicting slopping in a converter occurring during decarburization refining in the converter in which molten steel is produced from a molten pig iron by blowing oxidizing gas to the molten pig iron in the converter from a top blowing lance, or optionally further blowing oxidizing gas or inert gas from a bottom blowing tuyere to perform the decarburization refining of the molten pig iron. The method includes measuring an emission spectrum of a throat combustion flame blowing out from a throat of the converter, calculating emission intensity of the measured emission spectrum at a wavelength in a range of 580 to 620 nm, and predicting the occurrence of the slopping based on a time-series change of the calculated emission intensity.