3071 results about "Smelting process" patented technology

The invention relates to the technical field of tin smelting, and discloses an AI intelligent tin smelting control system and method, and the system comprises a data collection and preprocessing module, an intelligent decision and control module, and a real-time monitoring and early warning module. The method comprises the following steps: collecting process data in a tin smelting production process in real time, and cleaning the collected process data; extracting and selecting characteristics of which the influence on the smelting quality and efficiency exceeds a preset threshold value, and carrying out standardization processing on the data; receiving the standardized process data, training the model, processing the data monitored in real time, and outputting the adjusted process parameters; various key parameters and data in the production process are displayed in real time, the real-time data are analyzed, abnormal conditions are detected, early warning is carried out on faults, and response measures are automatically triggered. Intelligent and automatic tin smelting is achieved, and the efficiency, quality and safety of the smelting process can be effectively improved.

The invention discloses a method for inhibiting leaching of beryllium in lithium smelting slag, and the method comprises the following steps: mixing a curing and stabilizing agent and the lithium smelting slag in a ball milling manner, and enabling the leaching concentration of beryllium in the treated lithium smelting slag to meet the national standard; the treatment method can be directly carried out on the basis of the existing lithium smelting process flow; the curing and stabilizing agent comprises a calcium-containing compound; the calcium-containing compound comprises at least one of calcium phosphate, calcium sulfate, calcium carbonate and calcium hydroxide. Based on a compound beryllium fixing principle of lattice substitution and adsorption, after the medicament is used for treating the beryllium-containing lithium smelting slag, beryllium in the treated lithium smelting slag can be stably cured. Besides, the curing and stabilizing agent can be common industrial solid waste, is wide in raw material source, simple to operate, remarkable in effect and easy to realize large-scale application, treats waste with waste and has important significance on harmless treatment and resource utilization of the high-toxicity lithium slag.

The invention relates to a data-driven smelting control optimization method, and belongs to the technical field of smelting control. Comprising the steps that working condition classification is carried out through historical operation data of a current smelting furnace by adopting clustering analysis, association rule mining is carried out in each cluster, and a parameter rule base is established; obtaining the working condition category of the current smelting furnace temperature through the parameter rule base according to the smelting furnace operation production data; according to the current furnace temperature characteristic data and the working condition category, the change of the furnace temperature is predicted in real time; according to the current working condition type and the predicted furnace temperature data, a control parameter combination with the optimal energy consumption is selected from the parameter data set; and monitoring the state of the smelting furnace in real time, predicting the furnace temperature, adjusting the control parameter combination of smelting operation, and performing early warning through the furnace temperature fluctuation degree. Furnace temperature prediction is carried out through working condition recognition, then control parameter combinations are screened according to prediction results and working condition categories, and therefore the smelting process is regulated and controlled to achieve energy-saving optimization.

The invention provides an automatic adjustment method for gold bonding wire production parameters, and relates to the technical field of information, and the method comprises the steps: collecting a new smelting parameter data sample in real time, inputting the data sample into a parameter self-inspection neural network model, obtaining a predicted quality index value, comparing the predicted value with an actually measured quality index, and determining the production parameters of the gold bonding wire. Calculating a prediction error; and an incremental learning algorithm is adopted, online updating and fine tuning are performed on the parameter self-checking neural network model by using the newly collected data sample, and the connection weight of the parameter self-checking neural network model is adjusted according to the prediction error. Real-time self-inspection of parameters in the smelting process and dynamic prediction of quality indexes are achieved, abnormity can be found in time, production parameters can be optimized, and the quality stability and production efficiency of smelted products are effectively improved. Meanwhile, a self-adaptive optimization mechanism of the model ensures continuous improvement of prediction precision, and powerful support is provided for intelligent control of the smelting process.

The invention discloses an intelligent smelting process parameter optimization management method and system, and relates to the technical field of smelting process data processing, and the method comprises the steps: determining the initial time lag of a process parameter according to the input of the process parameter and the output of a smelting raw material, and considering the time lag characteristic of the process parameter during the adjustment. And the smelting state of the smelting equipment is defined, and the working state of the smelting equipment is defined, so that a reliable basis is provided for optimization of subsequent process parameters. The nonlinear relation between process parameter input and smelting raw material output and the coupling relation between process parameters are determined, the nonlinear relation is analyzed by considering the process parameter input, the smelting state and the smelting raw material output, and description is carried out through a polynomial regression mode. And the initial time lag is adjusted in combination with the nonlinear relation and the coupling relation. The process parameters are stably, rapidly and reasonably adjusted, the accuracy and adaptability of optimization and adjustment of the process parameters are improved, and it is guaranteed that the smelting process is efficiently and safely carried out.

The invention relates to a 1500MPa-grade nickel-based alloy for a second-generation high-temperature superconducting baseband and a preparation method of the 1500MPa-grade nickel-based alloy, and belongs to the technical field of materials. The nickel-based alloy comprises the following chemical components in percentage by weight: 15.0 to 17.0 percent of Cr, 15.0 to 17.0 percent of Mo, 4.5 to 9.5 percent of W, 5.0 to 7.0 percent of Fe, 0.3 to 0.7 percent of Mn, 0.01 to 0.05 percent of Si, 0.1 to 0.2 percent of V, 0.1 to 0.5 percent of Co, 0.1 to 0.2 percent of Al, 0.001 to 0.01 percent of B and Clt, 0.005%, Plt; 0.005%, Slt; 0.002%, Olt; 0.002%, Nlt; 0.002%, and the balance being nickel. On the basis of hastelloy, the strength of a matrix is improved by increasing the W element content, matching an optimized heat treatment process and combining cold deformation; the content of C is controlled, precipitation of carbides is controlled, and it is ensured that the carbides are completely dissolved in a matrix during homogenization treatment; and a pure smelting process is adopted, so that the oxygen content in the alloy is reduced, the inclusion content is controlled, and high purity is ensured. By adopting the component control strategy and the processing preparation and heat treatment process, the nickel-based alloy with the yield strength of 1,300 MPa or above, the tensile strength of 1,500 MPa or above and the ductility of 7.5% or above can be obtained after annealing is conducted for 5 min at the temperature of 900 DEG C, and the requirement of a second-generation high-temperature superconducting high-performance metal base band is met.

The invention discloses a side-blown furnace digital intelligent prediction system based on deep learning, and the system comprises a data collection and preprocessing module which is used for collecting the working data of a real-time sensor through the real-time sensor, and carrying out the preprocessing of the real-time sensor; the numerical calculation module is used for carrying out numerical simulation on a multi-physics field smelting environment in the side-blown furnace based on the preprocessed working data; the deep learning module is used for establishing and training a graph neural network GNN model based on the numerical simulation result, and obtaining a dynamic behavior rule of the molten pool smelting process through the GNN model; and the digital twinning module is used for constructing a digital twinning model consistent with the actual operation state of the side-blown furnace based on the dynamic behavior rule. According to the invention, accurate monitoring and prediction of the side-blown furnace can be realized, so that the smelting process is optimized and the operation efficiency is improved.

The invention relates to 390mm * 510mm section bloom B3 grinding ball steel and a preparation method thereof, and the preparation method comprises the following steps: loading a certain amount of molten iron and scrap steel for primary smelting in a converter, and sequentially adding an aluminum ingot, an alloy, pre-melting type calcium aluminate and refined lime when 1 / 4 of the steel is tapped; carrying out LF refining on the tapping molten steel subjected to primary smelting in the converter to obtain refined molten steel; the refined molten steel is subjected to RH vacuum refining, and RH vacuum refined molten steel is obtained through superheat degree control, RH working vacuum degree control, retention time control and soft blowing time control; and continuous casting is conducted, specifically, the RH vacuum refined molten steel is subjected to set pulling speed, crystallizer and tail end electromagnetic stirring and soft reduction treatment according to the pouring section, and the bloom B3 grinding ball steel with the section being 390 mm * 510 mm is obtained. According to the method, the converter primary smelting, the LF refining, the RH vacuum refining and the molten steel whole-process protection pouring smelting process are controlled, the cleanliness of the molten steel is guaranteed, and generation of large-particle inclusions is avoided; and process parameters are reasonably set in the continuous casting process, so that the internal quality of the bloom is obviously improved, and the production efficiency is greatly improved.

The invention relates to a 1400 MPa-grade nickel-based alloy for a second-generation high-temperature superconducting base band and a preparation method of the 1400 MPa-grade nickel-based alloy, and belongs to the technical field of materials. The nickel-based alloy comprises the following chemical components in percentage by weight: 15.0 to 17.0 percent of Cr, 13.0 to 15.0 percent of Mo, 5.5 to 9.0 percent of W, 5.0 to 7.0 percent of Fe, 0.4 to 0.6 percent of Mn, 0.01 to 0.05 percent of Si, 0.1 to 0.2 percent of V, 0.0 to 2.5 percent of Co, 0.1 to 0.2 percent of Al, 0.001 to 0.01 percent of B and Clt, 0.005%, Plt; 0.005%, Slt; 0.002%, Olt; 0.002%, Nlt; 0.002%, and the balance being nickel. On the basis of the Ni-Cr-Mo alloy, the composition design thought of increasing W and reducing Mo is adopted, the optimized hot working and heat treatment process is matched, and finally the strength of a base body is improved through cold deformation; the content of C is controlled, precipitation of carbides is controlled, and alloy elements are ensured to be completely dissolved into a matrix during homogenization treatment; and a pure smelting process is adopted, so that the oxygen content in the alloy is reduced, the inclusion content is controlled, and high purity is ensured.

The invention discloses a multi-parameter coupling intelligent regulation and control method and system in a vanadium ore smelting process, relates to the technical field of non-ferrous metal smelting automatic control, and solves the problems of feeding deviation and resource chain scission caused by slow response of an existing heat balance model to ore impurity fluctuation, online sensing lag and process island. The impurity concentration and the dielectric constant are obtained in real time through an LIBS / XRF combined probe and a microwave dielectric spectrum, rheological disturbance is dynamically corrected through extended Kalman filtering, a dynamic coupling response model is input, a thermodynamic interference factor is calculated, and a leaching and precipitation strategy is generated; performing mother liquor tail gas material flow collaborative optimization in parallel, constructing a multi-dimensional control vector U, performing iterative updating through near-end strategy optimization in a digital twin and issuing the multi-dimensional control vector U to an edge PLC (Programmable Logic Controller) in a distributed manner, and finally correcting a model weight through online XRD (X-Ray Diffraction) feedback; according to the method, the adaptive capacity to complex vanadium ore component disturbance, the response precision of online control and the inter-process resource circulation efficiency are remarkably improved.

The invention discloses an intelligent model data processing method applied to metal smelting, and relates to the technical field of metal smelting, and the method comprises the following specific steps: S100, collecting metal smelting data in real time, S200, establishing different sub-models, S300, outputting a prediction result based on each sub-model, and carrying out uncertainty evaluation. The invention designs a multi-target model output fusion mechanism capable of simultaneously considering the product quality, the energy consumption and the production efficiency in the metal smelting process, and through a weighted average method, the optimal decision output is obtained through the intelligent fusion of the output results, and the comprehensive optimal decision output is obtained, and S500, the actual data in the production process is continuously monitored, and the operation parameters of equipment are adjusted. The invention designs a multi-target model output fusion mechanism capable of simultaneously considering the product quality, the energy consumption and the production efficiency in the metal smelting process. And the model prediction results corresponding to different targets are intelligently fused to obtain a comprehensive optimal decision output, so that the metal smelting process can realize balance and optimization among a plurality of key indexes, and the demand of an enterprise for maximizing comprehensive benefits is met.

The invention relates to a 1300MPa-grade nickel-based alloy for a second-generation high-temperature superconducting baseband and a preparation method of the 1300MPa-grade nickel-based alloy, and belongs to the technical field of materials. The high-strength wear-resistant steel comprises the following chemical components in percentage by weight: 15.0%-17.0% of Cr, 15.0%-17.0% of Mo, 3.0%-4.5% of W, 5.0%-7.0% of Fe, 0.3%-0.7% of Mn, 0.01%-0.05% of Si, 0.1%-0.2% of V, 0.1%-0.5% of Co, 0.1%-0.2% of Al, 0.040%-0.080% of N, Clt and the balance of Fe. 0.002%, Plt; 0.005%, Slt; 0.002%, Olt; 0.002%, and the balance being nickel. The purification smelting process is adopted, the oxygen content in the alloy is reduced, the inclusion content is controlled, and the high purity of the material is guaranteed. By adopting the component control strategy, the heat treatment process and the final cold machining preparation, the nickel-based alloy with the yield strength being 1100 MPa or above, the tensile strength being 1300 MPa or above, the ductility being 15% or above and the product of strength and elongation being 20 GPa.% or above can be obtained after annealing is conducted for 5 min at the temperature of 900 DEG C, and the requirements of a second-generation high-temperature superconducting high-performance metal base band are met.

The present invention relates to the technical field of steel plate production, and particularly to a thick steel plate for high-strength storage tanks with a low ductile-brittle transition temperature and a preparation method thereof. The chemical components in the steel are as follows: C: 0.22% - 0.26%, Si: 0.13% - 0.144%, Mn: 0.73% - 0.92%, P≤0.015%, S≤0.01%, Cr: 0.03% - 0.049%, V: 0.01% - 0.019%, Nd: 0.00016% - 0.00047%, and the balance is Fe and impurities. Microalloying is used to ensure the excellent internal structure and service performance of the steel plate; the purity of the molten steel is improved by optimizing the smelting process; the internal structure of the steel plate is optimized and the plate shape is improved by adopting a four-stage slab heating process and a three-stage controlled rolling process; the simulated post-weld heat treatment process is used to improve the strength-ductility matching and adjust the microstructure of the material, ensuring the low-temperature service performance of the steel plate in the full thickness direction.

The invention discloses a process for smelting a ZL205A alloy. The process comprises the following steps: S1, ultrasonic pretreatment of raw materials: pretreating the raw materials of the ZL205A alloy by utilizing an ultrasonic technology; s2, segmented precise feeding and continuous stirring; s3, an argon dynamic protection system; S4, intelligent temperature control and energy recovery; s5, performing online component analysis and real-time adjustment; s6, a green pouring and cooling system; by optimizing the smelting process, adding a trace nucleating agent and other measures, the strength, toughness, corrosion resistance and other properties of the aluminum alloy can be remarkably improved, and the aluminum alloy can meet the requirement for high-performance application; the segmented precise feeding and continuous stirring technology is adopted, it is guaranteed that alloy elements are evenly distributed in the aluminum alloy, and the problem of unstable performance caused by uneven element distribution is solved; the argon dynamic protection system can effectively reduce oxidation and air suction phenomena in the smelting process, reduce generation of oxides and air holes and improve the quality of aluminum alloy.

The invention belongs to the field of high-temperature alloy manufacturing, and particularly discloses a low-segregation nickel-based high-temperature alloy, a preparation method of the low-segregation nickel-based high-temperature alloy and a segregation defect control method. The segregation defect control method comprises the steps that the melting speed of the nickel-based superalloy in the steady-state melting stage of vacuum consumable smelting is determined on the basis of the content of segregation-prone elements in the nickel-based superalloy; based on the determined melting speed of the steady-state melting stage, the filling ratio adopted for vacuum consumable smelting of the nickel-based superalloy is determined; and carrying out vacuum consumable smelting on the nickel-based superalloy according to the determined filling ratio and the determined melting speed in the steady-state smelting stage. According to the segregation defect control method, black spots, white spots and surface quality of the cast ingot in the nickel-based superalloy vacuum consumable smelting process can be effectively controlled.

The invention discloses a short-process continuous smelting method for nickel-containing copper concentrate. The method comprises the following steps: 1) smelting nickel-containing copper concentrate to obtain smelting slag and high-nickel copper matte which are layered up and down; (2) the high-nickel copper matte is subjected to suspension blowing, and nickel-copper blowing slag and crude copper which are layered up and down are obtained; and (3) the nickel-copper converting slag is subjected to reduction smelting, and vertically-layered reducing slag and copper-nickel alloy are obtained. By adjusting the reaction kinetics condition and the slag type structure of the blowing section, copper and nickel elements in the high-nickel copper concentrate are efficiently separated in the blowing section, the produced crude copper can meet the requirements of subsequent fire refining and electrolytic refining, a nickel removal link does not need to be added at the rear end, the smelting process is shortened, and the production cost is reduced. And the application of the high-nickel copper concentrate to large-scale continuous copper smelting becomes possible. The nickel-copper converting slag is reduced into the copper-nickel alloy, the link of returning the converting slag to be mixed in a traditional process is omitted, short-process recovery of the Ni element is achieved, the problem of circulating enrichment of the Ni element in a system is solved, and the method is a brand-new technical route for widening the application range of raw materials, reducing cost and improving efficiency in a copper smelting plant.

The composition general formula of the vanadium-based hydrogen storage alloy is VxTiyCrzCCe, x is larger than or equal to 0.7 and smaller than or equal to 0.8, y is larger than or equal to 0.04 and smaller than or equal to 0.1, z is larger than or equal to 0.1 and smaller than or equal to 0.18, x + y + z = 1, and a is larger than or equal to 0.001 and smaller than or equal to 0.005. The prepared vanadium-based hydrogen storage alloy has the advantages that the preparation process is simple, the hydrogen storage alloy which is easy to activate, high in capacity and good in cycling stability can be obtained by adding trace Ce, and the vanadium-based hydrogen storage alloy is suitable for large-scale generation preparation and commercial application. The alloy is prevented from being locally oxidized in the smelting process due to a small amount of Ce element, and the problem that the hydrogen absorption capacity is reduced due to excessive rare earth elements is avoided, so that the activation performance of the alloy is improved, and meanwhile, the high hydrogen storage capacity is obtained.

The invention relates to high-performance low-cost microalloyed steel for an automobile I-shaped front axle and a preparation method of the microalloyed steel, and belongs to the technical field of materials. The steel comprises the following chemical components in percentage by weight: 0.20 to 0.60 percent of C, 0.2 to 1.0 percent of Mn, 0.1 to 0.5 percent of Si, 0.6 to 1.2 percent of Cr, 0.01 to 0.10 percent of Nb, 0.01 to 0.06 percent of Mo and the balance of Plt, 0.01%, Slt; 0.01%, Olt; 0.0040%, and the balance being iron. According to the invention, the contents of Nb and C key alloy elements in the material are accurately controlled, so that Nb can be completely dissolved into a matrix in the smelting process, and the phenomenon of one-time NbC liquation is avoided. Heat treatment is directly carried out after smelting and casting, and the component control strategy is adopted, so that the precipitation of nano-sized dispersed NbC on an original austenite grain boundary is promoted, austenite grains are effectively pinned, and a microstructure with uniform and fine grain size is obtained; a martensitic structure is obtained through quenching, and uniform dispersion and precipitation of NbC carbide are realized in the martensitic structure through a subsequent tempering process, so that the strength and the toughness of the I-shaped front axle are ensured to reach the best match.

The invention discloses a method, a system and equipment for optimizing batching parameters in an industrial silicon smelting process. The method comprises the following steps: firstly, acquiring process parameters in an industrial silicon smelting process, standardizing the process parameters, then converting the process parameters into weight factors influencing a smelting result, and mapping a relation between the smelting result and the weight factors into a parameter equation based on a preset multiple linear regression model, obtaining a parameter set containing a weight factor and a linear regression coefficient; then, based on the parameter set, the initial raw material parameters and the reaction process parameters, an equivalent circuit model is constructed and simulated to generate smelting result data under different parameter combinations, and therefore parameter adjustment variables are obtained; according to the numerical range of the parameter adjustment variables and the initial raw material parameters, an optimal batching parameter combination is obtained; and finally, performing optimization treatment on batching parameters in the industrial silicon smelting process. According to the method, accurate control and rapid optimization adjustment of batching parameters can be stably achieved in the industrial silicon smelting process.

The invention relates to the technical field of copper metallurgy processes, and discloses a method and device for strengthening copper smelting through thiocarbon self-heating and chaotic stirring, and the method comprises the following steps: monitoring the temperature of a furnace kiln in real time by adopting a non-contact measurement technology; adding of mineral aggregates is adjusted according to the furnace temperature monitored in real time, the proportion of the added mineral aggregates is input into a sulfur-oxygen matching program, and the minimum threshold value of the oxygen inlet amount is calculated; inputting the furnace temperature, the slag thickness, the copper matte thickness and the minimum oxygen inlet amount threshold value which are monitored in real time into a nonlinear chaotic flow calculation program, and calculating the injection speed, the oxygen supply concentration and the injection angle; and after the smelting process is carried out, the temperature of the furnace kiln is fed back in real time according to the adjustment of the injection speed, the oxygen concentration and the injection angle. The device comprises a furnace top area, a furnace body area, a hearth area, a furnace wall, a feed opening, an uptake flue, a secondary air blowing gun, a copper matte discharge opening, a side blowing spray gun, a slagging chamber flue and a slagging opening. According to the invention, the energy utilization rate, the production efficiency and the product quality in the smelting process can be improved.

The invention relates to the technical field of metal materials, and discloses a preparation method of high-purity vanadium, which comprises the following steps: step 1, controlling the purity, granularity and content of raw materials for preparing a vanadium-aluminum intermediate alloy; 2, carrying out an aluminothermic reaction in a vacuum aluminothermic smelting furnace; thirdly, a plate ingot is smelted in a vacuum electron beam horizontal furnace for the first time; fourthly, the plate ingot is smelted in the vacuum electron beam horizontal furnace for the second time; and 5, smelting the high-purity vanadium ingot in a vacuum electron beam ingot pulling furnace. According to the method, traditional slag formers such as CaO are not used, so that alloy components are more stable in the smelting process, component fluctuation caused by the reaction of the slag formers and main reactants is reduced, the reaction temperature and degree are controlled by controlling the addition amount of the Al2O3 cooling material, energy is saved, and the smelting cost is reduced; the beneficial effects that a CaO slag former does not need to be used, and introduction of impurities is avoided are achieved.

The invention discloses an intelligent smelting factory informatization management method and system, relates to the technical field of data prediction, and comprises the steps of analyzing and reflecting the correlation relationship between information, providing a basis for subsequent multi-feature combination, and ensuring the reliability of multi-factor correlation calculation. According to the method, a plurality of features are combined according to the correlation relation among reflection information, the smelting energy consumption analysis model is trained through feature combination items and trend components, correlation combination is performed on the plurality of features, correlation among different features is considered, and the trend components are added, so that prediction of the smelting energy consumption analysis model is more accurate. The energy consumption abnormal section is analyzed to trace the energy consumption abnormal reason, the energy consumption deviation condition is determined through the predicted energy consumption normal range, so that the energy consumption abnormal reason is determined, follow-up monitoring and smelting process optimization are carried out on the energy consumption abnormal reason, and the reliability and effectiveness of informatization management of the smelting factory are guaranteed.

The invention belongs to the field of rail manufacturing, and specifically discloses a manufacturing method for improving the low temperature fracture resistance and contact fatigue damage resistance of rails and the rails obtained thereby. The method comprises the following steps: converter smelting, LF refining, RH vacuum treatment, billet continuous casting, billet cleaning and cooling, billet heating, rail rolling, online heat treatment and post-treatment, wherein: during the converter smelting process, bottom blowing of nitrogen is performed; after the RH vacuum treatment, iron-calcium wire feeding treatment is performed. Calculated by mass percentage, the chemical composition of the steel billet includes: C: 0.50-0.65%, Si: 0.45-0.95%, Mn: 0.35-0.85%, Cr: 030-0.80%, Cu: 0.20-0.55%, Ni: 0.10-0.30%, N: 0.007-0.030%, and the chemical composition of the steel billet also includes at least one of V, Nb, and Ti, wherein V: 0.02-0.15%, Ti: 0.001-0.030%, Nb: 0.01-0.08%, and the rest is Fe and unavoidable impurities. The steel rail obtained by the method provided by the present invention has excellent comprehensive properties such as resistance to low-temperature fracture, resistance to contact fatigue, corrosion resistance and weldability.

The invention relates to the technical field of task scheduling, in particular to a task scheduling optimization system for a smelting process, which comprises a furnace temperature identification module, a hot load analysis module, a load screening module, a sorting regulation and control module and a task joint control module. According to the method, a stable operation section is screened based on thermocouple time sequence temperature difference fluctuation characteristics, task identification is ensured to be in tight fit with a real metallurgical process state, furnace profile thermal parameters and raw material attributes are introduced to dynamically estimate task thermal loads, and the heat adaptation relation between tasks and equipment is determined; safety load interval limitation is set in the screening task and furnace body combination process, the safety and matching precision of resource allocation are improved, meanwhile, cooling period limitation is embedded in task sorting to recognize delay tasks, scheduling continuity and task connection reasonability are enhanced, the capacity of a scheduling strategy for responding to actual operation constraints is improved, and the service life of the scheduling strategy is prolonged. The overall optimization of accurate task screening, reasonable load distribution and ordered scheduling sequence is realized.

The invention relates to a nickel-based alloy composite plate and a preparation method thereof, and belongs to the technical field of alloy preparation. The alloy reinforcing agent is prepared under the sintering condition of high-temperature reducing gas protection by mixing the lanthanum element and the nanometer aluminum oxide, the granularity can be refined in the smelting process by adding the alloy reinforcing agent, and the wear resistance, hardness, strength and oxidation resistance of the alloy are effectively improved. Nickel is used as a matrix, an alloy reinforcing agent and elements such as molybdenum, copper, boron and hafnium are added, meanwhile, a mixture of potassium chloride and magnesium fluoride is used as a fluxing agent, uniform mixing and reaction of alloy components are promoted, and the nickel-based alloy smelted through step-by-step heating in vacuum has high hardness and strength and good abrasion resistance, corrosion resistance and high temperature resistance; and the stainless steel substrate and the nickel-based alloy plate are tightly combined through welding treatment, and the nickel-based alloy composite plate is suitable for manufacturing a vacuum chamber.

The invention relates to a slag performance regulation and control method for large-proportion collaborative smelting of multi-source lead-based solid waste in flash lead smelting, belongs to the technical field of non-ferrous metal smelting, and mainly solves the problem of collaborative regulation and control of the viscosity performance of slag by factors such as ZnO content, Al2O3 content, CaO / SiO2 mass ratio, alkalinity and the like of FeOx-CaO-SiO2-ZnO-PbO-Al2O3 system slag so as to realize low-carbon and safe smooth smelting. The method comprises the following steps: (1) reasonably controlling the contents of elements such as Zn and Al in a mixed material fed into a furnace and the addition amount of a CaO flux and a SiO2 flux, and starting smelting; (2) in the flash smelting process, the content of ZnO in the slag is controlled to be lower than 25 wt%, the content of Al2O3 in the slag is controlled to be lower than 6 wt%, the mass ratio interval of CaO / SiO2 is 0.30-0.50, the alkalinity interval is 1.8-2.3, and flash smelting and slag-lead separation are completed; and (3) normally discharging slag and lead. According to the method, in the production practice of flash lead smelting, the problem that slag and lead are difficult to separate due to collaborative smelting of large-proportion and multiple types of high-zinc and high-aluminum solid wastes can be solved, the safe, energy-saving and efficient lead smelting process is guaranteed, and the production capacity of the flash lead smelting furnace for treating the multi-source lead-based solid wastes is improved.

The invention provides an optimization method and device for industrial silicon smelting flue gas heat exchange efficiency, and relates to the technical field of industrial silicon smelting smoke.The optimization method comprises the steps that a main flue gas pipe geometric model is obtained according to first design information, a smelting associated information set is obtained, the smelting associated information set is adopted to conduct dust deposition attachment simulation on the main flue gas pipe geometric model, and a dust deposition distribution model is obtained; and analyzing and positioning a plurality of ash deposition high-risk areas in the ash deposition distribution model, taking the plurality of ash deposition high-risk areas as first heat exchange optimization information, and performing graphene material layout on the target main smoke pipe by adopting the first heat exchange optimization information to complete smelting flue gas heat exchange efficiency optimization of the industrial silicon smelting scene. The technical problem that in the prior art, the ash removal effect is poor, the cleaning difficulty is large, and consequently the heat exchange efficiency of the industrial silicon smelting waste heat boiler is reduced is solved. The technical effects that the heat exchange efficiency of the boiler in the industrial silicon smelting process is effectively improved, the influence of dust deposition on the heat exchange performance is reduced, the equipment maintenance cost is reduced, and the production efficiency is improved are achieved.

The invention discloses a nickel-magnesium intermediate alloy for a high-temperature alloy and a preparation method thereof.The nickel-magnesium intermediate alloy is composed of, by mass, 4%-50% of Mg and the balance Ni and inevitable impurities, and the method comprises the steps that firstly, electrolytic nickel and magnesium ingot raw materials are selected, cut and polished, and ingredients are calculated, weighed and subpackaged; 2, the raw materials are put into a crucible of an induction melting furnace to be smelted, and alloy melt is obtained; and thirdly, a steam suction filtration system is started, the alloy melt is poured into a cast iron ingot mold, and the nickel-magnesium intermediate alloy ingot is obtained after cooling. A proper amount of inert gas is introduced in the vacuum induction smelting process, smelting and pouring in a micro-negative pressure state are guaranteed, impurity introduction in the smelting and pouring processes is reduced by controlling smelting process parameters, meanwhile, gasification loss of the magnesium element is reduced, and the high-strength magnesium alloy with uniform components and high strength is obtained. The nickel-magnesium intermediate alloy is high in cleanliness and low in content of harmful gas elements and inclusions, and is suitable for the field of downstream high-temperature alloys.

The invention belongs to the technical field of circuit board metal smelting control, and discloses a circuit board metal smelting energy-saving parameter self-adaptive control system and method. The method comprises the following steps: carrying out real-time monitoring and fluctuation analysis on heating circuit voltage collected in unit time in the metal smelting process of the circuit board to obtain a voltage fluctuation level; processing the smelting state data acquired in unit time in the metal smelting process of the circuit board to obtain a smelting state characteristic data set, and identifying a current smelting stage; when the voltage fluctuation grade is greater than or equal to a preset voltage fluctuation grade threshold value, generating an energy-saving strategy control identifier in combination with the current smelting stage and the predicted smelting stage of the next unit time; dynamically adjusting energy-saving control parameters based on the voltage fluctuation grade, the smelting state characteristic data set and the energy-saving strategy control identifier; the intelligent self-adaptive control level of the circuit board metal smelting energy-saving parameters is enhanced, and energy-saving control is changed from passive execution to look-ahead response.

The invention relates to the technical field of metallurgical solid waste treatment, in particular to a process for extracting iron by reducing red mud through an electric furnace. In the converter steelmaking process, the dephosphorizing agent is a CaO-FeO-SiO2 slag system basically, and the red mud contains a proper amount of Al2O3, Na2O and the like, so that the dephosphorizing agent containing the red mud is changed into CaO-SiO2-FeO-Al2O3-Na2O slag, and the solubility of P is improved. The cost of the cost step is 350 yuan / steel, and the cost price of molten iron is more than 1300 yuan / steel. The price of the molten iron spindle is about 2400 yuan / ton. And the earnings of 2000 yuan / ton are higher. In the short-process smelting process of stainless steel, the high-iron red mud is directly reduced to extract iron by adding coke into the electric furnace to strike arc and blowing carbon powder, so that an iron water resource can be supplemented for the electric furnace, the problem that the red mud pollutes the environment is solved, and waste is turned into wealth. And a novel idea is provided for subsequent electric furnace smelting. According to the method, a novel thought and pioneering practice for treating the metallurgical solid waste by the stainless steel refining furnace are developed, considerable profits are created, and the competitiveness is improved.