583results about "Steel manufacturing process aspects" patented technology

The invention relates to the field of steelmaking. More specifically, the invention relates to a process for controlling nitrogen increase in electric furnace smelting. The invention provides a method for producing low-nitrogen steel from electric furnace full waste steel. The method specifically comprises the steps that waste steel is loaded into an electric furnace, CO2 gas is injected into the electric furnace before and after loading, air is exhausted, and micro-positive pressure in the electric furnace is kept. The method comprises the following steps: after an electric furnace forms a molten pool, injecting limestone powder at the top of the furnace with the injection amount of 60-80kg / t and the injection carrier gas of CO2 gas, after the electric furnace forms the molten pool, injecting oxygen and carbon powder by adopting a carbon-oxygen lance to make foamed slag, injecting CO2 gas into the molten pool to decarburize, produce two times of CO gas and intensify denitrification, and during tapping of the electric furnace, protecting steel flow from ending with air by adopting CO2 gas, and feeding into the next process for smelting after tapping of the electric furnace. Application proves that when the method is used for smelting low-nitrogen steel, nitrogen in the electric furnace can be controlled not to be increased, N is smaller than or equal to 0.003% after tapping of the electric furnace, the smelting rate of the low-nitrogen steel grade is increased, and low-carbon emission production of special varieties is achieved.

The invention relates to the technical field of converter steelmaking, particularly discloses a converter steelmaking process prediction method and system for multi-source-domain asynchronous data, and aims to solve the problems that converter steelmaking multi-source-domain data is lagged in information, asynchronous data feature extraction and fusion are difficult, and converter steelmaking working conditions are diversified and complicated. According to the method and system, a converter steelmaking working condition process prediction model is provided, the model uses a feature pyramid network to construct a multi-scale feature extraction network, and the multi-source domain asynchronous data feature learning ability of the model is improved through fusion; according to the model, a Transform module is adopted, a self-attention mechanism, a multi-head attention mechanism and residual connection are utilized to capture a dependency relationship in multi-scale fusion features, probability values of different working conditions are output, and an abnormal category corresponding to the maximum probability value is output as a working condition prediction result. Experiments prove that the method has relatively high accuracy on identification of five converter steelmaking working conditions.

Provided are a joint regulation method of material flow, energy flow, and carbon emission flow in a long-process steel enterprise, which belongs to a field of intelligent regulation and control technology of electric power system in the steel industry. The method includes: coupling a material-energy characteristic model of each production process of a steel enterprise and a carbon emission model of the steel enterprise, constructing a material flow-energy flow-carbon emission flow coupling model of the long-process steel enterprise, establishing an objective function using a minimize sum of an electricity purchase cost from a superior grid, a park carbon emission cost, and a production raw material cost as an object, and solving and obtaining an optimal operation mode of a joint regulation of the material flow-energy flow-carbon emission flow in the steel enterprise.

The invention relates to the technical field of ferrous metallurgy, and discloses a non-deslagging converter steelmaking method which comprises the following steps: step 1, establishing a slag-steel interface stability analysis model, and analyzing the stability of a slag and molten steel interface under the action of a gravity field, oxygen blowing gas flow and temperature gradient, including slag density, molten steel density, interfacial tension and oxygen blowing flow rate, so as to obtain a slag-steel interface stability analysis model; calculating the amplitude and wavelength of an interface; and 2, based on the interface disturbance physical parameters obtained in the step 1, optimizing oxygen blowing process parameters of the top-blowing spray gun, adjusting the oxygen blowing angle of the spray gun to be in the range of 15-25 degrees, and controlling the oxygen flow rate to be in the range of 600-700 Nm < 3 > / h. By establishing a slag steel interface stability analysis model and adopting a multi-field coupling theory of a gravity field, an oxygen blowing gas flow and a temperature gradient, the amplitude, the wavelength and the disturbance growth rate of interface disturbance are quantitatively analyzed, accurate prediction and optimal control of dynamic behaviors of the slag steel interface are achieved, and the effect that the interface is kept stable in the steelmaking process is achieved.

A furnace vessel of an arc furnace is loaded with solid metal. Afterward, an energy supply device of the arc furnace feeds electrical energy to electrodes of the arc furnace via a furnace transformer to form arcs between the electrodes and the metal, the arcs melting the metal. Finally, the molten metal is removed from the furnace vessel. The number of electrodes is at least three. For at least two of the electrodes, the energy supply device individually sets the operating frequency (fa, fb) of the relevant electrode. The current (Ic) through the third electrode is defined by the current (Ia, Ib) through the first and the second electrodes. Which of the electrode is the first electrode, which is the second electrode, and which is the third electrode is assigned dynamically.

The invention discloses a converter steelmaking molten pool carbon content detection method and system, a medium and a terminal, and the method comprises the steps: responding to a converter steelmaking signal, starting a three-section model, and obtaining the height of an oxygen lance and the oxygen flow of the oxygen lance in real time in the converter steelmaking process; a first carbon content detection value of a molten pool in the converter at the current moment is obtained through real-time analysis by utilizing a three-section type model and combining the height of an oxygen lance, the oxygen flow of the oxygen lance, the weight of waste steel added into the converter, the weight of molten iron and the carbon content; when the converter is in the last steelmaking stage, if a detection signal sent by the detection equipment is received, a second carbon content detection value of the molten pool in the converter at the current moment is obtained through real-time analysis based on the detection signal, and the first carbon content detection value and the second carbon content detection value are fused to obtain a carbon content detection result of the molten pool at the current moment. According to the method, the influence of the oxygen lance position, the oxygen flow and feeding on the decarburization rate is considered, the carbon content detection in the whole steelmaking process is realized, and the detection precision in the last steelmaking stage is optimized.

The invention discloses a converter steelmaking endpoint forecasting method and device and a storage medium, and the method comprises the steps: carrying out the multi-scale importance modeling and graph attention mechanism modeling of the multi-dimensional process characteristics of the current heat, and generating the importance weight and the structure perception weight of each dimension of process characteristics; fusing the importance weight and the structure sensing weight, and multiplying the fused weight with the corresponding dimension process characteristics to generate a characteristic regulation and control vector of the current heat; performing multi-scale convolution operation on the feature regulation and control vector, extracting local mode features under different receptive fields, and outputting a spatial feature vector after the local mode features are enhanced by a self-attention mechanism; a plurality of groups of Transformer encoders are adopted to respectively process the furnace feature sequences with different historical window lengths, and cross-furnace time sequence feature vectors are extracted; and carrying out dimension alignment on the spatial feature vector and the time sequence feature vector, carrying out dimension-by-dimension weighted fusion through a learnable fusion weight, and outputting a steelmaking end point state prediction value of the current heat through a regression prediction network.

The embodiment of the invention discloses an intelligent energy consumption regulation and control steel smelting system based on multi-energy complementation, and the system comprises a multi-energy complementation energy supply system which is used for integrating various energy forms, forming a dynamic cooperative energy supply network, and carrying out the energy cooperative operation according to an energy priority strategy and a dynamic matching mechanism; the intelligent regulation and control platform adopts a three-layer framework of'perception-decision-execution 'to coordinate energy flow and process operation between the multi-energy complementary energy supply system and the multi-energy coupling process equipment; the multi-energy coupling process equipment comprises hydrogen-based direct reduction ironmaking equipment, and hydrogen is used for replacing traditional coke to serve as a reducing agent for ironmaking; comprehensive energy supply monitoring and optimization can be carried out on the steel smelting process, various renewable energy sources are combined, and the problems that a single renewable energy source is intermittent, depends on a power grid and the like are effectively solved; meanwhile, the multi-energy complementary hydrogen storage process is coupled with the hydrogen metallurgy process, and the multi-energy cooperation problems of whole-process green power supply, waste heat utilization and the like are solved.

The invention provides a method for making foam slag in LF (ladle furnace) refining by using a waste graphite electrode, which specifically comprises the following steps: grinding the waste graphite electrode to obtain graphite electrode powder, and adding limestone as a foaming agent in the LF refining. 0-1.25 kg / t of steel limestone is added firstly, and 0.018-0.19 kg / t of steel graphite electrode powder is added every 2 min. Compared with the prior art, by utilizing the characteristics of high carbon content, high conductivity and low sulfur of the graphite electrode, the invention aims to realize submerged arc heating, reduce power consumption and shorten refining time so as to meet the requirement of continuously increasing LF smelting indexes under the high-quality development trend of steelmaking.

The invention discloses a control method for stabilizing the alkalinity of blast furnace slag. The method comprises the following steps: collecting blast furnace production data; calculating a blast furnace theoretical alkalinity lag period; establishing a dual-control model of a control model based on the theoretical slag alkalinity under the blast furnace tank and a control model based on the actual slag alkalinity of the blast furnace, and monitoring and analyzing the abnormal fluctuation reason of the actual slag alkalinity; and then targeted alkalinity control is carried out according to the reasons of abnormal fluctuation of alkalinity. According to the method, closed-loop control is achieved from the slag alkalinity fluctuation source and the slag fluctuation reason through the theoretical slag alkalinity and actual slag alkalinity dual-control model, the slag alkalinity fluctuation reason can be judged rapidly and comprehensively, targeted measures are taken for different reasons, the slag alkalinity is stabilized more accurately and rapidly, the blast furnace is kept stable, and the method is suitable for large-scale popularization and application. The steel production quality is improved.

The invention relates to a high-carbon steel wire rod, a smelting system and a short-process high-efficiency low-cost smelting method. On the basis of real-time monitoring and identification at different stages of an electric furnace smelting process, a power supply curve, an oxygen supply curve and a charging and carbon spraying curve are formulated according to the characteristics of different stages of electric furnace smelting; and efficient and accurate automatic control over the electric furnace smelting process of the high-quality high-carbon steel wire is achieved.

Method of producing steel with using steel scrap in electric arc furnace The method of producing steel using an Electrical Arc Furnace (EAF) comprising successively loading a load (L) in the EAF, the load (L) containing steel scrap (SC), energizing the electrodes of the EAF for melting the load (L) and generating a melt (M); introducing a desulphurizing slagging agent in the EAF for generating a desulphurizing slag (S1) above the melt (M) and then removing the desulphurizing slag (S1) from the EAF, and injecting oxygen in the EAF for decarburizing the melt (M).

A blast furnace operation method according to one aspect of the present disclosure comprises: a parameter estimation step for estimating blast parameters and a pulverized coal ratio in a second operation, such that the amount molten iron produced, the molten iron temperature, and the furnace top gas temperature in the second operation match those in a reference operation; a change information acquisition step for acquiring information on a temporal change in one or both of the molten iron temperature and the amount of molten iron produced when performing the second operation based on the blast parameters and the pulverized coal ratio estimated in the parameter estimation step with a delay of a predetermined time after switching from the reference operation to the first operation; a repeating step for performing the change information acquisition step a plurality of times while changing the predetermined time; and an optimum delay time acquisition step for determining, as an optimum delay time, a predetermined time such that the temporal change in the molten iron temperature or the amount of molten iron produced is the smallest, on the basis of the information acquired in the repeating step. After switching from the reference operation to the first operation, the second operation based on the blast parameters and the pulverized coal ratio estimated in the parameter estimation step is started with a delay of the optimum delay time.

The invention belongs to the technical field of metallurgical industry, and discloses a real-time control method and system for a carbon spraying and oxygen blowing process of an electric arc furnace. The method includes the following steps that at least three high-temperature-resistant distance measuring sensors are evenly installed on the top of the electric arc furnace, and the distance between the top of the electric arc furnace and foamed slag is measured; calculating an average distance value, and calculating the height of the foaming slag according to the hearth height. A telescopic air gun is used for blowing away local foaming slag, and the height of the molten steel level is measured. The thickness of the foam slag is calculated and compared with a preset threshold value, and the carbon spraying and oxygen blowing technological parameters are adjusted accordingly. And establishing a correlation model of the carbon spraying and oxygen blowing process parameters and the thickness of the foam slag, predicting the thickness change trend of the foam slag, and performing pre-adjustment. The system comprises a distance measuring sensor, a telescopic air gun, a data acquisition module, a calculation module, a prediction module and a control module. The method and system can monitor and control the thickness of the foamed slag in real time, effectively prevent the slag flowing phenomenon and the difficulty of electrode submerged arc, and improve the smelting efficiency and quality of the electric arc furnace.

The invention relates to a method for optimizing a pig iron desulfurization process (1), wherein the pig iron desulfurization process (1) is carried out by dispensing one or more desulfurization agents (2, 3, 4) into a pig iron ladle (5) or a torpedo car, wherein a plurality of treatment patterns are available which differ with respect to the type of desulfurization agents (2, 3, 4) dispensed. The optimization is based on creating a separate model (8) for each of the plurality of treatment patterns in order to optimize the added amounts of the desulfurization agents (2, 3, 4) for the associated treatment pattern, and training (9) the created separate models (8) for each of the plurality of treatment patterns after a predefined number of performed pig iron desulfurization processes (1) with the corresponding treatment pattern. Future pig iron desulfurization processes (1) are optimized on the basis of the predictions of the separate models (8), wherein the optimization determines a treatment pattern and the added amounts of the desulfurization agents (2, 3, 4) for the treatment pattern by means of a comparison of the predictions of the separate models (8). The invention also relates to a system and a computer program which are designed to carry out the method according to the invention.

The invention belongs to the technical field of ferrous metallurgy, and particularly relates to a molten steel smelting method adopting fluoride-free refining slag in LF (ladle furnace) refining, which comprises the following steps: taking a slag sample from the LF refining slag refined by fluorine-containing refining slag, analyzing the components of the slag sample, calculating the metallurgical properties including melting point and viscosity of the slag sample by using FactSage software, and calculating the content of the fluoride-free refining slag according to the calculation result. The composition of the fluoride-free refining slag system replacing the fluorine-containing refining slag is obtained through phase diagram calculation; obtaining the molten steel oxygen content and temperature at the converter smelting end point, and determining the amount of slag needing to be added according to the molten steel oxygen content and temperature at the converter smelting end point; lime and synthetic refining slag are added in the converter tapping process for slagging to achieve first modification; and in the LF refining process, residual lime and synthetic refining slag are added for slagging to realize secondary modification, a slag system is adjusted to a required fluoride-free refining slag system composition, and LF refining is realized by adopting molten steel of fluoride-free refining slag for smelting.

The invention provides a load balance control system of a converter tilting device and a control method thereof, and belongs to the field of converter control. The control system comprises a plurality of motors including a first motor and a second motor; the plurality of feedback encoders, the plurality of controllers and the plurality of frequency converters correspond to the plurality of motors; the motor feedback encoders are arranged on rotating shafts of all the motors and used for obtaining the first rotating speed and the second rotating speed; the master controller is used for generating an integral component and a first control reference value, and the slave controller is used for generating a second control reference value; the frequency converters are in data communication connection, the main frequency converter is used for synchronizing integral components to the driven frequency converter, and the main frequency converter and the driven frequency converter are respectively used for controlling the first motor and the second motor to execute first and second control reference values. The method is mainly used for solving the problems of overload, reverse dragging, unstable control and the like caused by non-uniform load distribution when the converter is driven by multiple motors to tilt, the tilting stability is improved, and the wear rate of equipment is reduced.

The invention provides an electroslag remelting smelting endpoint element dynamic forecasting and process decision optimization method and system, and the method comprises the steps: obtaining a historical data set and a real-time data flow in a smelting process, and carrying out the preprocessing of data; an online stochastic gradient descent and incremental learning algorithm is introduced, an element dynamic prediction model is constructed, sensor data in the smelting process are received in real time, and an element concentration prediction model is dynamically optimized; on the basis of a depth deterministic strategy gradient algorithm, an optimization decision model is constructed, and a smelting operation strategy is adjusted in real time according to element components, smelting working conditions and other environment parameters predicted online by the element dynamic forecasting model; and a real-time feedback mechanism is set, so that the element dynamic prediction model and the optimization decision model work cooperatively, and element concentration prediction and real-time synchronous adjustment of a control strategy are realized. The smelting parameters can be adjusted in real time, element prediction precision is improved, energy consumption is reduced, manual intervention is reduced, and smelting efficiency and quality stability are remarkably improved.

The invention discloses a blast furnace working condition knowledge graph construction method and device, and belongs to the field of blast furnace ironmaking intelligent control. The method comprises the following steps: fusing multi-source data, integrating sensor real-time data, process parameters, operation logs and expert rules, and enhancing abnormal working condition data generation capability by using a time sequence generative adversarial network; a three-layer dynamic body structure with the core abnormal furnace condition as the center is constructed, and a dynamic edge weight updating mechanism is designed; extracting multi-region spatial-temporal characteristics of the blast furnace by adopting a spatial-temporal diagram convolutional network, and generating an interpretable knowledge triple in combination with a causal discovery algorithm FGES; and realizing real-time updating of the knowledge graph based on a streaming graph learning framework, generating a regulation and control instruction through multi-agent reinforcement learning, and issuing the regulation and control instruction to a blast furnace control system through a digital twin interface. The method can clearly represent the symptom incidence relation of the abnormal furnace condition of the blast furnace, rapidly position the abnormal source and generate the regulation and control strategy, and has important practical significance for improving the intelligent level of blast furnace ironmaking.

The invention discloses a smelting method of cold direct reduced iron in a Consteel electric furnace, belonging to the technical field of electric furnace steelmaking. The smelting method comprises the following steps: at the beginning of smelting, low-grade power supply is adopted, and at the same time of power-on, oxygen lances and carbon lances on the furnace wall are used to blow oxygen and spray carbon to produce foamed slag for submerged arc. After 1-3 minutes, scrap steel is continuously added by the Consteel system, and cold direct reduced iron is added through the fifth hole of the electric furnace. The molten steel in the furnace is heated by the electric arc, and the molten steel melts the metal materials in the furnace; during the whole smelting process, lime and light burned dolomite are added in batches. The addition amount of lime is 30-50 kg / t of steel, and the addition amount of light burned dolomite is 25-30 kg / t of steel. The invention helps to maintain the whole-process flat bath smelting, reduce the power consumption of electric furnace smelting, and reduce the smelting cost; it provides a technical solution for a short-process demonstration plant for the efficient use of direct reduced iron in an electric furnace, filling the domestic technical research gap in the short-process industry of electric furnaces.

The present invention relates to reduction of a metal oxide material (5) and to a metal material production configuration (1) adapted for reduction of a metal oxide material (5) holding thermal energy into a reduced metal material (16).The metal oxide material (5) is charged into an upper interior portion (UP) of a reduction facility (7). A hydrogen containing reducing agent (6) is introduced into the reduction facility (7) and is adapted to react with the metal oxide material (5) holding thermal energy for reducing the metal oxide material (5) by utilizing the thermal energy of the metal oxide material (5) to heat or further heat the introduced hydrogen containing reducing agent (6).The reduction facility (7) of the metal material production configuration (1) is configured for providing a heat treatment process of the reduced metal material (16).A control circuitry (50) is configured to adjust the temperature of the hydrogen containing reducing agent (6) and control the temperature of the introduced hydrogen containing reducing agent (6) for reaching at least one desired passivation parameter value (DPPV) of the reduced metal material (16).

The invention relates to the technical field of converter safety monitoring, in particular to a method for predicting the thickness of refractory bricks based on converter wall temperature. The temperature distribution and the residual thickness of the refractory bricks are estimated according to the external furnace body temperature and the melt smelting temperature, and then the overhaul of the converter is judged according to the temperature distribution and the residual thickness of the refractory bricks, so that the real-time safety monitoring in the operation process of the converter is realized. The problem of how to monitor the operation risk of the converter is solved.

The invention provides a method and system for coupling biomass solid waste to generate power and preparing a biomass charcoal foaming agent for steelmaking, and relates to the field of solid waste treatment. The method comprises the following steps: gasifying one part of biomass solid waste through a gasification furnace to obtain gasified carbon and biomass gas, and carbonizing the other part of biomass solid waste through a carbonization furnace; the carbonization comprises a low-temperature pyrolysis stage, a high-temperature pyrolysis stage and a slow cooling stage which are carried out in sequence; when the total amount of the pyrolysis gas generated by the carbonization furnace is less than or equal to 15-25Nm < 3 > / h, completing carbonization to obtain pyrolytic carbon; and compounding the gasified carbon and the pyrolytic carbon to obtain the biomass carbon foaming agent for steelmaking. According to the method provided by the invention, the obtained gas is utilized to generate power while the charcoal product suitable for the electric furnace steelmaking foaming agent is prepared, so that the deep utilization of biomass solid wastes is realized.

The present application belongs to the field of smelting coal gas recovery, and particularly relates to an optimized control method and system for combustible gas recovery. The method divides the smelting process into N measurement time periods, and calculates the average secondary combustion coefficient of each time period in real time. Meanwhile, M target smelting time zones and their weights are set, and a dynamic target value sequence is established. Based on the initial fan speed, the measured coefficient is adjusted through multiple iterations of the furnace, and when the measured coefficient is greater than the target value, the speed is reduced in steps, and a thermal imager and a differential pressure instrument are introduced to monitor the smoke emission. A smoke emission rate statistics and tolerance threshold judgment mechanism is established to trigger speed backtracking adjustment, and finally the average secondary combustion coefficient of each time period is minimized to generate an optimal fan speed model. The present application maximizes the improvement of the calorific value of coal gas and the recovery of carbon monoxide under the premise of preventing smoke from the furnace mouth.

The invention relates to the technical field of blast furnace tiled material layers, and particularly discloses a material distribution method for a blast furnace tiled material layer, which comprises the following steps: dividing furnace charge into large, medium and small particles according to particle diameters, filtering through different pore sieves, then distributing to a blast furnace through a material distribution chute according to a particle size sequence, and dividing a blast furnace material distribution layer into a plurality of areas, a laser radar is used for scanning to obtain sub-region height and wrinkle area information, a height difference value ratio mean value and a cloth wrinkle area ratio are calculated to obtain a cloth flatness coefficient, the cloth flatness coefficient is compared with a threshold value to generate a flatness analysis signal, the cloth flatness coefficient is monitored accordingly, a time-cloth flatness coefficient change curve is drawn, and a material layer fluctuation ratio is calculated. And if the fluctuation ratio of the material layer exceeds a threshold value, generating a tiling analysis signal, and finally, calculating the adjustment value of the rotation angle of the material distribution chute based on the signal and related parameters, so as to monitor and adjust the material distribution condition of the blast furnace, effectively improve the material distribution uniformity and stability of the blast furnace and guarantee stable production of the blast furnace.

Provided are a molten iron component estimation device, a component estimation method, and a desulfurization method, whereby it is possible to estimate the component of molten iron after desulfurization with high accuracy in the desulfurization of molten iron using a mechanical stirring facility. A component estimation device (14) that estimates the S concentration in molten iron (3) during desulfurization of the molten iron (3) using a mechanical agitation desulfurization facility (1) is provided with: a data input unit (140) that inputs current operation data during the desulfurization; the current operation data at least comprises the temperature of the molten iron (3) measured by a non-contact temperature measuring device (12) after the stirring of the molten iron (3) is started and before the input of the desulfurizing agent (4) is started, namely the temperature of the molten iron in the desulfurization treatment; and a model calculation unit (142) that estimates the S concentration in the molten iron (3) after desulfurization on the basis of current operation data and a machine learning model that represents the relationship between the temperature of the molten iron during desulfurization and the amount of the desulfurizer (4) introduced and the reaction rate constant during desulfurization on the basis of past operation data during desulfurization.

A dynamic control method and apparatus for an electric arc furnace smelting state, a device, and a medium. The method comprises: collecting smelting data generated by an electric arc furnace during a smelting process; and, calculating an arc length and a foamed slag height using the smelting data, further determining a submerged arc condition of the electric arc furnace on the basis of the arc length and the foamed slag height, and adjusting smelting parameters of the electric arc furnace on the basis of the condition; or, calculating differences between data sub-items and corresponding historical warning thresholds, and adjusting smelting parameters of the electric arc furnace on the basis of the calculation results. The method achieves real-time monitoring and intelligent analysis of the smelting state of the electric arc furnace, ensures the flexibility and efficiency of electric arc furnace operation, and improves energy utilization.

A production method of pig iron using a blast furnace with a tuyere includes: charging a first layer containing an iron ore material and a second layer containing coke alternately in the blast furnace; and reducing and melting the iron ore material in the charged first layer while injecting an auxiliary reductant into the blast furnace by hot air blown from the tuyere, in which: an aggregate for letting through the hot air to a central portion of the blast furnace is blended into the first layer; and the aggregate contains a reduced iron molded product obtained through compression molding of reduced iron.

The invention discloses a multi-dimensional fusion sensor data anomaly detection method based on a hydrogen-based shaft furnace, and belongs to the technical field of metallurgical equipment monitoring. The method comprises the steps of data preprocessing, single-variable anomaly detection, multivariable consistency detection, anomaly type judgment and alarm output. The single variable detection adopts a rolling median absolute deviation method, drift detection, continuous tiny variable threshold and border crossing detection; the multivariate detection calculates reconstruction residuals of each sensor through principal component analysis (PCA) and identifies overall consistency anomalies. And the system judges the fault type according to the comprehensive score of the multiple detection results and outputs a detailed alarm record and a statistical report. According to the method, multi-algorithm fusion analysis is carried out on time sequence data collected by a plurality of sensors in the operation process of the shaft furnace, so that the abnormal states of the sensors are accurately recognized. The method can be widely applied to real-time monitoring of the hydrogen-based shaft furnace smelting process, the accuracy and robustness of anomaly detection are improved, and false alarms and missing alarms are reduced.

The invention discloses a converter optimal molten iron scrap ratio dynamic adjustment method which is characterized by comprising the following steps: monitoring the temperature and chemical component data of molten iron entering a converter in real time; establishing a prediction model based on historical data and an intelligent algorithm, and predicting the molten iron temperature and chemical component change trend; calculating first influence data of the scrap steel adding amount on the molten iron temperature according to the physical thermal correction model, and calculating second influence data of element oxidation heat on the total heat according to the chemical thermal correction model; and the molten iron scrap ratio is dynamically adjusted according to the results of the first influence data and the second influence data, and the generated scrap ratio is transmitted to a converter control system in real time. According to the prediction model based on historical data and an intelligent algorithm, the temperature and component change trend of the molten iron is predicted in advance, so that the scrap ratio is adjusted in advance, the steelmaking efficiency is improved, the cost is reduced, and the environmental influence is reduced.