Direct alloying of nickel oxide in a hot simulator of LD converter was investigated in laboratory.Reduction rate of nickel oxide in steelmaking process was analyzed with the test results. Under the condition oflower s...Direct alloying of nickel oxide in a hot simulator of LD converter was investigated in laboratory.Reduction rate of nickel oxide in steelmaking process was analyzed with the test results. Under the condition oflower slag viscosity, the reduction rate of NiO increases and the [Ni] yield rises. When the slag viscosity is higher, a lot of metal particles with higher Ni content are contained in the slag so as to decrease the [Ni] yield.展开更多
Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC...Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC test.To maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the field.The number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as inputs.First,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time series.Through optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,respectively.Its field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carried out,and dynamic control methods based on prediction values were proposed.展开更多
Through summary and extraction of current steelmaking design,process and equipment technologies and production technologies for 300 t grade converters in Baosteel,the article analyzes and elaborates the significance o...Through summary and extraction of current steelmaking design,process and equipment technologies and production technologies for 300 t grade converters in Baosteel,the article analyzes and elaborates the significance of independent integration of 300 t grade converters in Zhanjiang,major targets of the independent integration in converter process technologies,equipment packages and controls,the innovated critical technologies and comparison with overseas advanced technologies,major technical difficulties in the integration in Baosteel and their solutions,as well as general mindset and final objectives of the project.The total integration of technology for Shanghai No.1 Steel Making Plant of Baosteel was undertaken by Nippon Steel.And Kawasaki Steel was responsible for the total integration of technology for 4# and 5# converters of Shanghai No.2 Steelmaking Plant of Baosteel.Based on digestion,absorption and innovation of the introduced technologies,Baosteel has firstly achieved the independent integration of 6# converter,5# RH and 3# LF projects in the Shanghai No.2 Steelmaking Plant of Baosteel.Therefore, Baosteel shall take advantages of the favorable conditions and experiences and advanced steel making technologies of Baosteeel to master the imported new steelmaking technologies in the world and then form the advanced complete set steel making technologies and equipment at home and abroad.The achievement of independent integration of Zhanjiang Steel Making Project will make the breakthrough for the construction of large - sized steel making plant in Baosteel.300 t converter technology integration is undertaken by Baosteel independently in instead of by the foreign side in the past.展开更多
The process model for BOF process can be applied to predict the liquid steel composition and bath temperature during the whole steelmaking process. On the basis of the traditional three-stage decarburization theory, t...The process model for BOF process can be applied to predict the liquid steel composition and bath temperature during the whole steelmaking process. On the basis of the traditional three-stage decarburization theory, the concept of mixing degree was put forward, which was used to indicate the effect of oxygen jet on decarburization. Furthermore, a more practical process model for BOF steelmaking was developed by analyzing the effect of silicon, manganese, oxygen injection rate, oxygen lance height, and bath temperature on decarburization. Process verification and end-point verification for the process model have been carried out, and the verification results show that the predic- tion accuracy of carbon content reaches 82.6% （the range of carbon content at the end-point is less than 0. 1wt%） and 85.7% （the range of carbon content at end-point is 0. 1wt% -0.7wt%） when the absolute error is less than 0.02wt% and 0.05wt%, respectively.展开更多
Firstly, physical and chemical properties of dust removed from BOF gas are analyzed, and then the cold banding technology of dust removed from BOF gas and its application are introduced. Tests have proved that using c...Firstly, physical and chemical properties of dust removed from BOF gas are analyzed, and then the cold banding technology of dust removed from BOF gas and its application are introduced. Tests have proved that using cooled agglomerated pellets made of the dust removed from BOF gas and small amounts of modified starch as a coolant and slagging agent in steel production can bring about considerable economic, social and environmental benefits.展开更多
文摘Direct alloying of nickel oxide in a hot simulator of LD converter was investigated in laboratory.Reduction rate of nickel oxide in steelmaking process was analyzed with the test results. Under the condition oflower slag viscosity, the reduction rate of NiO increases and the [Ni] yield rises. When the slag viscosity is higher, a lot of metal particles with higher Ni content are contained in the slag so as to decrease the [Ni] yield.
基金This research has been supported by the Natural Science Foundation of Hebei Province,China(E2022318002).Thanks are given to Tangsteel Co.,Ltd.of Hesteel Group and Digital Co.,Ltd.of Hesteel Group for providing detailed data,hardware and software support for model development and field production test.
文摘Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC test.To maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the field.The number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as inputs.First,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time series.Through optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,respectively.Its field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carried out,and dynamic control methods based on prediction values were proposed.
文摘Through summary and extraction of current steelmaking design,process and equipment technologies and production technologies for 300 t grade converters in Baosteel,the article analyzes and elaborates the significance of independent integration of 300 t grade converters in Zhanjiang,major targets of the independent integration in converter process technologies,equipment packages and controls,the innovated critical technologies and comparison with overseas advanced technologies,major technical difficulties in the integration in Baosteel and their solutions,as well as general mindset and final objectives of the project.The total integration of technology for Shanghai No.1 Steel Making Plant of Baosteel was undertaken by Nippon Steel.And Kawasaki Steel was responsible for the total integration of technology for 4# and 5# converters of Shanghai No.2 Steelmaking Plant of Baosteel.Based on digestion,absorption and innovation of the introduced technologies,Baosteel has firstly achieved the independent integration of 6# converter,5# RH and 3# LF projects in the Shanghai No.2 Steelmaking Plant of Baosteel.Therefore, Baosteel shall take advantages of the favorable conditions and experiences and advanced steel making technologies of Baosteeel to master the imported new steelmaking technologies in the world and then form the advanced complete set steel making technologies and equipment at home and abroad.The achievement of independent integration of Zhanjiang Steel Making Project will make the breakthrough for the construction of large - sized steel making plant in Baosteel.300 t converter technology integration is undertaken by Baosteel independently in instead of by the foreign side in the past.
基金supported by the New Century Excellent Talents Program of the Ministry of Education of China (No.NCET 07-0067)the National Natural Science Foundation of China (No.50874014)
文摘The process model for BOF process can be applied to predict the liquid steel composition and bath temperature during the whole steelmaking process. On the basis of the traditional three-stage decarburization theory, the concept of mixing degree was put forward, which was used to indicate the effect of oxygen jet on decarburization. Furthermore, a more practical process model for BOF steelmaking was developed by analyzing the effect of silicon, manganese, oxygen injection rate, oxygen lance height, and bath temperature on decarburization. Process verification and end-point verification for the process model have been carried out, and the verification results show that the predic- tion accuracy of carbon content reaches 82.6% （the range of carbon content at the end-point is less than 0. 1wt%） and 85.7% （the range of carbon content at end-point is 0. 1wt% -0.7wt%） when the absolute error is less than 0.02wt% and 0.05wt%, respectively.
文摘Firstly, physical and chemical properties of dust removed from BOF gas are analyzed, and then the cold banding technology of dust removed from BOF gas and its application are introduced. Tests have proved that using cooled agglomerated pellets made of the dust removed from BOF gas and small amounts of modified starch as a coolant and slagging agent in steel production can bring about considerable economic, social and environmental benefits.
