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	2021 Vol. 56 No. 9
	Published: 2021-09-15



	Technical Reviews Steelmaking Metal Forming Materials Metallurgical Artificial Intelligence Technology

Technical Reviews

	1	YANG Jian, WU Si-wei
		Property prediction of steel rolling process based on machine learning
		In order to achieve rapid optimization design of hot rolling process,the property prediction of steel based on industrial data has attracted great attention of researchers. The research progress of steel rolling process property prediction using machine learning was reviewed. Firstly,the main machine learning algorithms commonly used in steel rolling process property prediction were introduced,including artificial neural network,fuzzy neural network,support vector machine,random forest,intelligent optimization algorithm and so on. Secondly,the research progress and the applications of steel rolling process property prediction model were summarized respectively. Finally,the prospect of the research on the property prediction of steel rolling process was presented,and the possible development directions were pointed out,such as the improvement of data quality,the modeling of small sample data,the encryption of modeling data,the research of model interpretability,the prediction of steel microstructure and the effective process optimization design by using the model.
		2021 Vol. 56 (9): 1-9 [Abstract] ( 686 ) [HTML 1KB] [PDF 3379KB] ( 969 )

Metallurgical Artificial Intelligence Technology

	10	LI Hong-yang, LIU Xiao-jie, LI Xin, BU Xiang-ping, LI Hong-wei, LÜ Qing
		Application of industrial Internet platform for blast furnace iron making
		With the continuous improvement of the technology of the industrial internet platform, the digitalization and intelligent upgrading of the blast furnace ironmaking sector is imperative. To solve the problems in data collection, storage, analysis, and application in the field of blast furnace ironmaking, it is necessary to build an industrial internet platform for blast furnace ironmaking. The current status of industrial internet platforms and builds an industrial internet platform for blast furnace ironmaking in response to the actual needs of data analysis in the field of ironmaking were described. The article explains the logic of the edge layer, infrastructure layer, platform layer, and application layer in the overall architecture of the platform. The functions of data transmission, data storage, data processing, data scheduling, business modeling, data interaction and analysis, and intelligent applications are realized through industrial internet technology. The process of building smart applications with the starting point of solving real pain points in production is explored. The establishment of an industrial internet platform for blast furnace ironmaking has important practical significance for the transformation and upgrading of the ironmaking industry.
		2021 Vol. 56 (9): 10-18 [Abstract] ( 258 ) [HTML 1KB] [PDF 2421KB] ( 754 )

	19	YU Jia-xue, SUN Jie, ZHANG Dian-hua
		Accurate prediction of head thickness of hot-rolled strip based on deep learning
		Aiming at the problem of low precision of hot rolled strip head thickness, a hit prediction method of hot rolled strip head thickness based on deep learning was proposed. In the process of finish rolling, the tension of the head end of the steel is small, and the temperature is usually lower. At the same time, the process parameters of the rolling mill are complex, and it is difficult to set accurately. The thickness of the rolled strip head is often unqualified. This study intends to use the nonlinear fitting ability of the deep neural network to design the prediction model of strip head thickness, to provide a reference for the parameter setting of rolling mill, improve the hit rate of head thickness and reduce the waste of steel. The deep neural network (DNN) consists of the input layer, hidden layer, and output layer structure. The prediction model is designed by TensorFlow open-source machine learning framework and implemented by program. By adjusting the parameters of the neural network and studying their effects on the model performance, the prediction model is optimized. Finally, the model of head thickness prediction was trained and tested with the test data of various thicknesses of strip steel, and the result showed that the accuracy of classification prediction was more than 80%.
		2021 Vol. 56 (9): 19-25 [Abstract] ( 262 ) [HTML 1KB] [PDF 3230KB] ( 597 )

	26	XU Yang-huan, WANG Dong-cheng, WANG Yong-mei, YUAN Wen-yue, YU Hua-xin, LIU Hong-min
		Dimension reduction method of cold rolling strip flatness data based on autoencoder
		In order to realize the intelligent manufacturing of plate and strip rolling process, it is necessary to deeply explore the connotation of intelligent manufacturing. For specific problems, it is of great significance to apply the unsupervised learning and the reinforcement learning theory to production practice. The flatness detection data in the process of strip rolling is taken as the research object and the autoencoder in the unsupervised learning theory is used to automatically learn the basic flatness mode, so as to reduce the amount of storage and transmission of flatness data, realize the abstract representation of flatness distribution, and lay the foundation for the flatness anomaly detection, the intelligent prediction and the intelligent control. Compared with the traditional flatness data dimension reduction method based on Legendre polynomial, the accuracy of flatness reconstruction can be significantly improved and the approximate lossless compression of the flatness data can be realized applying the present method.
		2021 Vol. 56 (9): 26-35 [Abstract] ( 207 ) [HTML 1KB] [PDF 12659KB] ( 379 )

	36	PENG Gong-zhuang, CHENG Yin-liang, LIANG Yue-yong, HE An-rui
		Collaborative scheduling of vehicles and unmanned cranes in a cold-rolled steel product warehouse
		To study the collaborative scheduling of delivery vehicles and unmanned cranes in steel plant logistics warehouses,an integer programming model aiming at minimizing the service time of the cranes was established in view of the characteristics of multiple varieties and small batches of products and frequent entry and exit in cold-rolled steel product warehouse,and then the rules of cranes allocation were set up. Experiments were carried out under different order sizes by using heuristics-based scheduling,traditional genetic algorithm based scheduling and adaptive genetic algorithm (AGA) based scheduling. Experiment results shown that,compared with the other two scheduling schemes,the adaptive genetic algorithm based scheduling scheme can find out optimal scheduling results quickly and efficiently under different order sizes,which can guide the crane scheduling of unmanned warehouses in steel plants and effectively optimize the warehouse logistics inventory management.
		2021 Vol. 56 (9): 36-42 [Abstract] ( 255 ) [HTML 1KB] [PDF 2304KB] ( 531 )

	43	LI Jiang-yun, YANG Zhi-fang, ZHENG Jun-feng, ZHAO Yi-kai
		Applications of iron and steel industry with deep learning technologies
		Since artificial intelligence was proposed at the Dartmouth Conference in 1956,it has brought the greatest impact and change to human society in the third wave. The deep learning technology,as one of the main driving forces in this period,is helpful to use in Intelligent steel manufacturing. In order to explore the application prospects of deep learning technologies in the iron and steel industry,several key technologies using deep learning method were explored. Along with the related work by the authors,the research goals and advantages of deep learning based technologies applying to steel intelligent manufacturing were illustrated,which provides reference for the advantages of artificial intelligence technology to empower the development of steel manufacturing manufacturing.
		2021 Vol. 56 (9): 43-49 [Abstract] ( 363 ) [HTML 1KB] [PDF 3560KB] ( 861 )

	50	SHI Can-tao, WU Xiu-ting, ZHU Tao
		Supporting connotative development of iron and steel industry with digital infrastructure
		In order to study the ecological utilization of data in the iron and steel industry, the new development situation of China's iron and steel industry, as well as the new capacity requirements for iron and steel enterprises in the new development stage were introduced. The existing problems and development trend of iron and steel industry were described, then the characteristics of the data resources of the iron and steel industry and the basis of digital enabling, data elements and land, labor, capital, technology and other traditional factors of production continue to cross fusion were analyzed, and the key areas of data development in the iron and steel industry from the three aspects of enhancing the core competitiveness of enterprises, optimizing the allocation of industry resources and supporting the government's industrial governance were summarized. It is proposed to build a new credit system of the industry through the "digital infrastructure" based on blockchain to support the connotative development of iron and steel industry.
		2021 Vol. 56 (9): 50-55 [Abstract] ( 203 ) [HTML 1KB] [PDF 2370KB] ( 479 )

	56	WANG Jian-quan, LI Wei, MA Zhang-chao, SUN Lei, ZHANG Chao-yi
		5G industrial Internet empowers smart steel
		The convergence of 5G and industrial Internet will inject new momentum into smart manufacturing. In order to discuss the application and development of 5G industrial Internet in the field of smart steel,first started with the needs of smart manufacturing in the steel industry,featured with new trends including flat system architecture,unified communication protocols,and wireless network connections. Further,considering 5G standard progress and commercial deployment,it introduces the enhanced features provided by 5G for industrial applications. With the existing demo applications of 5G industrial Internet,it points out the current limitations and challenges of 5G for steelmaking. Finally,it analyzes the series of problems posed for the short-term and mid- to long-term development stages of 5G industrial Internet empowered smart steel,including industry adaptation,network,terminal,application scenarios,standard evolution and provides corresponding suggestions for future research directions.
		2021 Vol. 56 (9): 56-61 [Abstract] ( 445 ) [HTML 1KB] [PDF 3173KB] ( 789 )

Steelmaking

	62	JIANG Xiao-fang, YANG Wen-yuan, WU Ya-ming, WANG Ming-lin, LI Hong-tao, HU Yan-bin
		High oxygen supply intensity steelmaking with dual-angle oxygen lance nozzle in large converter
		In order to increase the oxygen flow rate of the 300 t converter in Baosteel's steelmaking plant from 60 000 to 69 000 m³/h, a 6-hole dual-angle oxygen lance nozzle was designed. Based on the test results of the first dual-angle nozzle, combined with the measurement of the jet flow field of the oxygen lance nozzle in the laboratory, and the water model study of the effect of the jet and the molten bath, the nozzle design was improved. In order to formulate the correct oxygen supply system and nozzle design, the pipeline pressure loss of Baosteel No.1 Steelmaking Plant was measured. The main parameters of the optimized No.3 6-hole dual-angle nozzle are, oxygen outlet Mach number Ma≥2.1, the oxygen flow of the small-angle nozzle is larger than 57% of the total oxygen flow, and the angle of the large-angle nozzle is larger than 13°, the angle of the small-angle nozzle is about 10°. The effect of steelmaking with No.3 6-hole nozzle is, oxygen flow rate is 69 000 m³/h, oxygen blowing time is shortened by 2.0 min/ch on average, dephosphorization rate is 87.5% on average, and oxygen lance nozzle life is 190 times on average. Through this research work, we have mastered the design and manufacture of the dual-angle 6-hole nozzle for high oxygen intensity blowing (3.833 m³/(t·min)) and the blowing operation technology of the large converter.
		2021 Vol. 56 (9): 62-73 [Abstract] ( 213 ) [HTML 1KB] [PDF 4956KB] ( 472 )

	74	YANG Wen, ZHANG Yan-hui, ZHANG Li-feng, JIANG Jin-dong, WU Cong-ying
		Mechanism of drawing fracture of hard wire steel and optimization of continuous casting process
		Hard wire steel requires not only good mechanical properties,but also good processing properties. However,wire breakage often occurs in the drawing process of the wire rod of hard wire steel,which brings great harm to the continuity of processing. In order to reduce the wire breakage during the drawing of hard wire steel,the drawing fracture mechanism was studied,and the optimization of the corresponding continuous casting process was carried out. The drawing fractured wire sample of 82B hard wire steel was analyzed firstly. Through the analysis on the fractograph and longitudinal section of the fracture specimen,combined with the internal quality inspection of corresponding continuous casting billet,the influence mechanism of central defects and segregation of billet on drawing fracture of hard wire steel was obtained,which promoted the formation of cementite film in the center of wire rod and led to the generation and propagation of cracks. Then,by applying final electromagnetic stirring (F-EMS) at the solidification end of continuous casting with current of 350 A and frequency of 6.0 Hz,and reducing the superheat of molten steel to below 30 ℃,the central shrinkage and central segregation of 82B hard wire steel billet were reduced to 0.5 and 1.08, respectively,and the wire breaking rate of 82B hard wire steel was significantly reduced from 10-15 times per 100 tons before optimization to 4-5 times per 100 tons.
		2021 Vol. 56 (9): 74-79 [Abstract] ( 219 ) [HTML 1KB] [PDF 5617KB] ( 436 )

	80	ZHAO Jia-qi, CAI Xiao-feng, MA Jian-chao, LI Jie, ZHANG Lian-bing
		Improvement on mechanism of nozzle clogging caused by CaS inclusions in Al-killed cold heading steel
		Through the research of nozzle clogging in the casting process of Al-killed cold heading steel, the nodules are C12A7, CaS, a little mount of MgO and TFe, etc, and the main reason for the nozzle clogging is the inclusions with a high percentage of CaS which is up to 36.91%. Combined with the production process, it is found that a large number of CaS inclusions will be formed when the w([S]) or the calcium content in molten steel is too high. Through a series of measures, such as improving deoxidization and slagging process, optimizing calcium treatment process, etc, w([S]) in the molten steel before calcium treatment is controlled below 0.005 0%, and the w([Ca]) after calcium treatment is controlled within 0.001 4%-0.002 6%, the result is that the modification of Al₂O₃ inclusions in molten steel is sufficient, and the formation of CaS inclusions causing nozzle clogging is avoided. The problem of nozzle clogging caused by CaS inclusions is effectively solved, and the castability of molten steel of aluminum killed cold heading steel is improved, the number of continuous casting heats is increased from 10 to 16 on average.
		2021 Vol. 56 (9): 80-87 [Abstract] ( 240 ) [HTML 1KB] [PDF 4393KB] ( 644 )

Metal Forming

	88	QIAN Sheng, ZHANG Wen-jun, LIN Wei, GU Qing, BAI Zhen-hua
		Formation mechanism and prediction model for C-warping defect of strip steel in continuous annealing process of hot galvalume unit
		In order to effectively reduce the risk of C-warping of the strip steel and improve the uniformity of its surface coating, the formation mechanism of C-warping in continuous annealing process of hot dip galvanizing were studied. In view of equipment and process characteristics of continuous annealing process of hot galvalume unit, the forming mechanism of C-warping defects is analyzed in detail from the point of elastic-plastic mechanics, and then the mechanical model of C-warping is deduced. The strip element method is used to establish the prediction model of strip C-warping in the process of the unit. Based on this, the optimization recursion method is used to solve the difficulty of the prediction model of strip C-warping successfully. Finally, based on this, the software, which predicts for C-warping defects of the strip in the continuous annealing process of the galvalume unit, is formulated and applied to the scene. The model used to forecast the shape of two typical specifications strip steel in different processes of the furnace. The analysis results show that the deviation between the forecasted and measured values of unit outlet strip shape can meet the requirements of product precision. The model can predict the strip shape of the process in the furnace in real-time, and provide theoretical guidance for the subsequent process parameter optimization. So the model has the value of further popularization and application.
		2021 Vol. 56 (9): 88-95 [Abstract] ( 223 ) [HTML 1KB] [PDF 4087KB] ( 362 )

	96	SHI Jian-rui, SUN Wen-quan, CHEN Lu-zhen, YUAN Tie-heng, ZHANG Xi-bang, LI Li-gang
		Rolling mill slip prediction model based on limit static friction torque
		In the process of cold continuous rolling, when the rolling torque is greater than the limit static friction torque between the roll and the rolled piece, the relative sliding will occur between the roll and the rolled piece, which will lead to the occurrence of sliding. For reducing the surface defect caused by slip, based on the basic formula of the plastic deformation in strip rolling, the unit rolling force distribution in the forward and backward sliding regions is simplified linearly, and then the ultimate static friction torque model is derived. The accuracy of the model is verified by the measured data. From the changing trend of the difference between rolling torque and ultimate static friction torque, it is found that the difference value gradually decreases to zero with the increase of rolling kilometers. At the same time, the method that the difference value is less than the set threshold is used to determine whether the work roll is slipping or not. It has been proved that the model is of great practical significance for the judgment of the work roll slippage in the tandem cold rolling.
		2021 Vol. 56 (9): 96-101 [Abstract] ( 191 ) [HTML 1KB] [PDF 1804KB] ( 386 )

	102	SONG Jun, REN Ting-zhi, WEI Zhen, LIU Bao-quan, WANG Kui-yue, SONG Bao-yu
		Optimal control of work roll shifting in tandem cold rolling mill based on multi-objective optimization
		In order to solve the problem that on-line shifting of work roll and shape of work roll cone section often cause strip breaking when continuous two coils are flying gauge change and the mill is in high speed continuous production. Based on the multi-objective optimization theory, the multi-objective function of the work roll shifting was constructed and the optimal roll shifting interval under different roll shapes was calculated, the edge drop control effect of tandem cold mill was improved. At the same time, according to the dynamic compensation control of work roll shifting speed, the optimal control value of roll shifting speed under different rolling force conditions was determined to reduce the influence of roll wear and axial force, ensure the stability of the high-speed rolling process, reduce the times of strip breaking in the process of work roll shifting, and improve the mill operating rate and product quality.
		2021 Vol. 56 (9): 102-109 [Abstract] ( 247 ) [HTML 1KB] [PDF 2545KB] ( 531 )

Materials

	110	LI Zhi-feng, HE Shuai, XING Shu-qing, MA Yong-lin, LIU Zhen-yu
		Effects of chromium addition on high temperature oxidation behavior of hot rolled low carbon steel
		In order to study the compound effect of chromium and heating process parameters (heating temperature,holding time) on the oxide scale formed on the surface of hot rolled low carbon steel,the effect of chromium content on high temperature oxidation behavior of low carbon steel in air at 1 100-1 250 ℃ was studied by thermogravimetry analysis. The oxidation rate constant was calculated. The phase composition,the micro-structure and the element proportion of oxide scale under different experimental conditions were compared. The results show that the high temperature oxidation presented a two-stage model. The oxidation kinetics curve was linear in the early stage of oxidation,and then changed to parabolic in the middle and late stage of oxidation. The transformation time from linear to parabolic was shortened with the increase of chromium content in the steel. The structure of the oxide scale was composed of the outermost Fe₂O₃ layer,the middle Fe₃O₄ layer and FeO layer,and the chromium rich spinel (FeCr₂O₄) layer near the substrate after the adding of the chromium. In the oxidation process,the FeCr₂O₄ layer suppressed the outward diffusion of the iron ions and the electrons,and reduced the oxidation rate. Meanwhile,the high temperature oxidation resistance of low carbon steel was significantly improved.
		2021 Vol. 56 (9): 110-117 [Abstract] ( 231 ) [HTML 1KB] [PDF 2649KB] ( 538 )

	118	LUO Xiao-bing, ZHU Fei, YANG Cai-fu, CHAI Feng, ZHANG Zheng-yan
		Relationships between microstructure and mechanical properties in dual-phase Cu-bearing steel strengthened by nano sized precipitates
		To improve the mechanical properties of HSLA Cu-bearing steel,multi-stage heat treatment (QLT) consisting of quenching,lamellarization and tempering was applied in a low-carbon Ni-Cr-Mo-V-Cu low alloy steel. Superior combination of high strength and low-temperature toughness was achieved and yield strength 895 MPa,tensile strength 950 MPa and low-temperature (-80 ℃) toughness 188 J was obtained. The dual-phase microstructure evolution with inter-critical annealing temperature (within Ac1-Ac3 region) in the tested steel treated by QLT route was invested by methods of SEM,XRD and TEM,and corresponding relationships between microstructure and mechanical properties were also clarified. Yield strength of the QLT specimens shows a quadratic parabolic relationship with the volume percent of the tempered secondary martensite,and the tensile strength exhibits a linear positive relationship with the volume percent of the tempered secondary martensite. Elongation after fracture is positively correlated with the volume percent of inter-critical ferrite. Among all QT and QLT specimens,QL₇₂₀T one (inter-critical annealing temperature is 720 ℃) shows excellent combination of strength and low-temperature toughness. High strength of QL₇₂₀T specimen comes from tempered secondary martensite which is strengthened by nanosized MC (M is any combination of Nb,Mo,V and Ti) and Cu particles. Excellent low-temperature toughness of QL₇₂₀T specimen is caused by following factors, the refining effect of dual-phase microstructure led by the parallel distribution of tempered secondary martensite and inter-critical ferrite; the refined brittle cementite or alloyed cementite caused by lots of heterogeneous-phase interfaces; low strength difference between tempered secondary martensite and inter-critical ferrite.
		2021 Vol. 56 (9): 118-128 [Abstract] ( 151 ) [HTML 1KB] [PDF 5827KB] ( 496 )

	129	LI Cheng-gang, SHAN Wen-chao, LIU Yi-si, YANG Ming, WANG Hao, CAO Guang-ming
		Corrosion resistance process based on control of oxide scale in whole process of hot rolling
		According to the actual working conditions of hot rolling production process,the evolution law of triple oxide iron sheet in hot rolling and coiling stage is systematically studied,aiming at improving the corrosion resistance of steel by adjusting the hot rolling production process to control the structure of oxide iron sheet and using the oxide iron sheet generated after hot rolling as protective barrier without increasing the production cost. The experimental results show that at different rolling temperatures,the structure of tri-oxide iron sheet is Fe₂O₃,Fe₃O₄ and FeO from the outside to the inside,and the proportion of FeO is the largest due to the high density of cation vacancy in FeO. With the increase of rolling temperature,the thickness of FeO layer in the iron sheet is gradually thickened,and the proportion is also gradually increased. By simulating the continuous cooling experiment,it is found that the transformation relationship of the oxide sheet structure is in the form of "C" curve. In the temperature range of 450-550 ℃,the eutectoid reaction degree of FeO reaches the peak,and it can be seen that the eutectoid transformation can be effectively inhibited by coiling at high temperature. A large number of experimental studies have shown that obtaining the structure type of complete oxide sheet with pro-eutectoid Fe₃O₄ is the main control direction to improve the corrosion resistance of hot-rolled steel effectively. So this article in a domestic steel strip production line based on the corrosion resistance of iron oxide control process to try rolling test and salt spray test,the results show that full dense iron oxide,and its structure type is mainly pro-eutectoid Fe₃O₄,so use of rolling technology to adjust the changing structure of the steel plate surface scale,steel corrosion resistant performance is improved significantly
		2021 Vol. 56 (9): 129-135 [Abstract] ( 225 ) [HTML 1KB] [PDF 2855KB] ( 542 )

	136	LIU Tian-xiang, YANG Mao-sheng, LI Shao-hong
		Fatigue crack initiation and propagation behavior of high temperature carburized bearing steel during rotary bending
		In order to improve the service life of aviation bearing, with the help of QBWP-10000X rotary bending fatigue testing machine,the rotary bending fatigue properties and crack initiation and propagation behavior of high temperature carburized bearing steel were studied. The results show that the median fatigue strength of the steel reaches 913.3 MPa. A large amount of M₂₃C₆ and a small amount of M₆C carbides in the effective carburized layer significantly improve the surface hardness of the test steel. Different carbon concentrations in the carburized layer lead to martensite transformation successively and form 408 MPa surface compressive stress,which further improves the fatigue property of the steel. The fatigue cracks mainly originate from surface defects and subsurface carbides,accounting for 71.4% and 28.6% respectively. The results show that the characteristic size of crack initiation and the bearing stress have a significant effect on the stress intensity factor and the number of cycles. The shape of deep furrow directly affects the number of cycles due to the stress concentration. The larger the characteristic size of carbide under the same loading stress,the lower the number of cycles. After the crack initiation,it propagates rapidly along the carbide boundary of carburized layer and slowly to the core. Finally,quasi cleavage and ductile mixed fracture occur near the edge of the specimen on the opposite side of the fatigue source.
		2021 Vol. 56 (9): 136-143 [Abstract] ( 180 ) [HTML 1KB] [PDF 4665KB] ( 422 )

	144	ZOU Hang, LIU Man, XU Guang
		Effect of cooling conditions after rolling on microstructure and properties of a low-carbon bainitic steel
		In order to investigate the effect of different cooling conditions after rolling on microstructure and mechanical properties of a high-strength low-carbon bainitic steel,the dilatometry,field emission SEM,TEM and tensile tests were utilized to clarify the microstructural evolution and property changes of a high-strength low-carbon bainitic steel under different cooling conditions. The results show that,with a final cooling temperature of 510 ℃ and 450 ℃ in the bainite transformation area,the microstructure mainly composed of GB and BF respectively,and more island like martensite was found in the former condition. Moreover,GB and BF microstructure were refined and the portion of island like martensite was reduced as the cooling rate increased. At different cooling conditions,a lower final cooling temperature always led to a higher phase transformation speed,and the highest phase transformation speed acquired at the condition of a cooling rate of 50 ℃/s. With a higher final cooling temperature,better plasticity and smaller strength variation acquired. On the contrary contrast,superior strength acquired,but lower plasticity and remarkably strength fluctuation.
		2021 Vol. 56 (9): 144-150 [Abstract] ( 222 ) [HTML 1KB] [PDF 4291KB] ( 526 )

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