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Optimal proportioning of iron ore in sintering process based on improved multi-objective beluga whale optimisation algorithm

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Journal of Iron and Steel Research International 2024年第7期31卷 1597-1609页

作者： Zong-ping Li Xu-dong Li Xue-tong Yan Wu Wen Xiao-xin Zeng Rong-jia Zhu Ya-hui Wang Ling-zhi Yi Zhongye Changtian International Engineering Co. Ltd.Changsha 410205HunanChina College of Automation and Electronic Information Xiangtan UniversityXiangtan 411105HunanChina College of Electrical and Information Engineering Hunan UniversityChangsha 410082HunanChina

Proportioning is an important part of sintering,as it affects the cost of sintering and the quality of sintered *** address the problems posed by the complex raw material information and numerous constraints in the sintering process,a multi-objective optimisation model for sintering proportioning was established,which takes the proportioning cost and TFe as the optimisation ***,an improved multi-objective beluga whale optimisation(IMOBWO)algorithm was proposed to solve the nonlinear,multi-constrained multi-objective optimisation *** algorithm uses the con-strained non-dominance criterion to deal with the constraint problem in the ***,the algorithm employs an opposite learning strategy and a population guidance mechanism based on angular competition and two-population competition strategy to enhance convergence and population *** actual proportioning of a steel plant indicates that the IMOBWO algorithm applied to the ore proportioning process has good convergence and obtains the uniformly distributed Pareto ***,compared with the actual proportioning scheme,the proportioning cost is reduced by 4.3361¥/t,and the TFe content in the mixture is increased by 0.0367%in the optimal compromise ***,the proposed method effectively balances the cost and total iron,facilitating the comprehensive utilisation of sintered iron ore resources while ensuring quality assurance.

关键词： sintering process Proportioning Iron ore Multi-objective beluga whale optimisation algorithm Proportioning cost

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Application of deep learning in iron ore sintering process:a review

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Journal of Iron and Steel Research International 2024年第5期31卷 1033-1049页

作者： Yu-han Gong Chong-hao Wang Jie Li Muhammad Nasiruddin Mahyuddin Mohamad Tarmizi Abu Seman School of Electrical and Electronic Engineering Universiti Sains Malaysia14300 Nibong TebalPenangMalaysia College of Electrical Engineering North China University of Science and TechnologyTangshan 063210HebeiChina Technology Transfer Center North China University of Science and TechnologyTangshan 063210HebeiChina School of Metallurgy and Energy North China University of Science and TechnologyTangshan 063210HebeiChina

In the wake of the era of big data,the techniques of deep learning have become an essential research direction in the machine learning field and are beginning to be applied in the steel *** sintering process is an extremely complex industrial *** the main process of the blast furnace ironmaking industry,it has great economic value and environmental protection significance for iron and steel *** is also one of the fields where deep learning is still in the exploration *** order to explore the application prospects of deep learning techniques in iron ore sintering,a comprehensive summary and conclusion of deep learning models for intelligent sintering were presented after reviewing the sintering process and deep learning models in a large number of research ***,the mechanisms and characteristics of parameters in sintering processes were introduced and analysed in detail,and then,the development of iron ore sintering simulation techniques was ***,deep learning techniques were introduced,including commonly used models of deep learning and their ***,the current status of applications of various types of deep learning models in sintering processes was elaborated in detail from the aspects of prediction,controlling,and optimisation of key *** speaking,deep learning models that could be more effectively implemented in more situations of the sintering and even steel industry chain will promote the intelligent development of the metallurgical industry.

关键词： Deep learning sintering process Modelling Simulation technology Intelligent sintering

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Effect of sintering process on microstructure and magnetic properties of high frequency power ferrite

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Rare Metals 2006年第z1期25卷 509-514页

作者： SUN Ke LAN Zhongwen CHEN Shengming SUN Yueming YU Zhong State Key Laboratory of Electronic Thin Films and Integrated Devices UESTCChengdu 610054China Jiangsu Research Center of Magnetic Materials and Devices Engineering and Technology Wuxi 214199China

An oxide ceramic process was adopted to prepare high frequency manganese-zinc(MnZn)power *** combination with the microstructure analysis of material,the influences of sintering process on initial permeability(μ_(i))and high frequency loss in unit volume(P_(cv))of MnZn power ferrite were *** results show that in order to obtain fine microstructure and high frequency properties,the preferable sintering temperature and atmosphere are 1230℃and oxygen partial pressure(P_(O_(2)))of 4%,respectively.

关键词： manganese-zinc ferrite microstructure initial permeability sintering process

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Ore-blending optimization model for sintering process based on characteristics of iron ores

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International Journal of Minerals,Metallurgy and Materials 2012年第3期19卷 217-224页

作者： Sheng-li Wu Dauter Oliveira Yu-ming Dai Jian Xu School of Metallurgical and Ecological Engineering University of Science and Technology Beijing Beijing 100083 China VALE Shanghai Office Shanghai 200070 China

An ore-blending optimization model for the sintering process is an intelligent system that includes iron ore characteristics, expert knowledge and material balance. In the present work, 14 indices are proposed to represent chemical composition, granulating properties and high temperature properties of iron ores. After the relationships between iron ore characteristics and sintering performance are established, the ＂two-step＂ method and the simplex method are introduced to build the model by distinguishing the calculation of optimized blending proportion of iron ores from that of other sintering materials in order to improve calculation efficiency. The ore-blending optimization model, programmed by Access and Visual Basic, is applied to practical production in steel mills and the results prove that the present model can take advantage of the available iron ore resource with stable sinter yield and quality performance but at a lower cost.

关键词： ore-blending optimization mathematical model sintering process iron ores

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Basic characteristics of Australian iron ore concentrate and its effects on sinter properties during the high-limonite sintering process

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International Journal of Minerals,Metallurgy and Materials 2017年第9期24卷 991-998页

作者： Dong-hui Liu Hao Liu Jian-liang Zhang Zheng-jian Liu Xun Xue Guang-wei Wang Qing-feng Kang School of Metallurgy and Ecological Engineering University of Science and Technology BeijingBeijing 100083China Xuanhua Iron&Steel Group Co.Ltd. Xuanhua 075100China Beijing Shenwu Environment&Energy Technology Co. Ltd.Beijing 102200China

The basic characteristics of Australian iron ore concentrate (Ore-A) and its effects on sinter properties during a high-limonite sintering process were studied using micro-sinter and sinter pot methods. The results show that the Ore-A exhibits good granulation properties, strong liquid flow capability, high bonding phase strength and crystal strength, but poor assimilability. With increasing Ore-A ratio, the tumbler index and the reduction index (RI) of the sinter first increase and then decrease, whereas the softening interval (Delta T) and the softening start temperature (T (10%)) of the sinter exhibit the opposite behavior; the reduction degradation index (RDI+3.15) of the sinter increases linearly, but the sinter yield exhibits no obvious effects. With increasing Ore-A ratio, the distribution and crystallization of the minerals are improved, the main bonding phase first changes from silico-ferrite of calcium and aluminum (SFCA) to kirschsteinite, silicate, and SFCA and then transforms to 2CaO center dot SiO2 and SFCA. Given the utilization of Ore-A and the improvement of the sinter properties, the Ore-A ratio in the high-limonite sintering process is suggested to be controlled at approximately 6wt%.

关键词： iron ore concentrate limonite basic characteristics sinter properties sintering process

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Research on sintering process of YSZ electrolyte

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Rare Metals 2006年第z2期25卷 209-212页

作者： HAN Minfang TANG Xiuling PENG Suping Union Research Center of Fuel Cell School of Chemical & Environment Engineering China University of Mining & Technology Beijing 100083 China Union Research Center of Fuel Cell School of Chemical & Environment Engineering China University of Mining & Technology Beijing 100083 China Union Research Center of Fuel Cell School of Chemical & Environment Engineering China University of Mining & Technology Beijing 100083 China

Yttria stabilized zirconia (YSZ) has widely been used as electrolyte in solid oxide fuel cell (SOFC). The microstructure of YSZ related to the fabrication process was discussed in the paper. With YSZ nano-powders about 40-100 nm as raw material, the YSZ adobe was manufactured by tape calendering process. The named three-step sintering process was performed at 1000 ℃ for 2 h, then raised the temperature with normal rate and as soon as up to 1400 ℃, the furnace was controlled at 1250-1300 ℃ for 10-20 h. The high dense YSZs with the relative density of 96%-99% were obtained; the grain size of YSZ could be reduced to 0.5-3 μm. The above result is benefited to co-fired in the electrode-supported SOFCs.

关键词： yttria stabilized zirconia (YSZ) electrolyte sintering process

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Research and Application of Expert System Skeleton for Controlling sintering process

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Journal of Iron and Steel Research International 2008年第5期15卷 6-8页

作者： LONG Hong-ming FAN Xiao-hui JIANG Tao DAI Lin-qing School of Metallurgy and Resource Anhui University of Technology Ma＇anshan 243002 Anhui China School of Resources processing and Bioengineering Central South University Changsha 410083 Hunan China

An expert system skeleton tool of sintering process was constructed using object-oriented method, which can actualize two functions, i. e. , the shell function and the program function. The skeleton tool offered a platform to build a prototype system, to program class code, and to develop the expert system. Four branch expert systems were developed using the skeleton tool including the control of chemical composition, the control of sintering process state, the control of expended energy, and the diagnosis of abnormity. It is found that the performance of all systems is satisfactory in practice.

关键词： sintering process expert system skeleton tool knowledge base illation engine

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Simulation and Prediction of Alkalinity in sintering process Based on Grey Least Squares Support Vector Machine

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Journal of Iron and Steel Research International 2009年第5期16卷 1-6页

作者： SONG Qiang WANG Ai-min Mechanical Engineering Department Anyang Institute of Technology Anyang 455000 Henan China Computer and Information Engineering College Anyang Normal University Anyang 455000 Henan China

The prediction of the alkalinity is difficult during the sintering process. Whether or not the level of the alkalinity of sintering process is successful is directly related to the quality of sinter. There is no very good method for predicting the alkalinity by now owing to the high complexity, high nonlinearity, strong coupling, high time delay, and etc. Therefore, a new technique, the grey squares support machine, was introduced. The grey support vector machine model of the alkalinity enabled the development of new equation and algorithm to predict the alkalinity. During modelling, the fluctuation of data sequence was weakened by the grey theory and the support vector machine was capable of processing nonlinear adaptable information, and the grey support vector machine has a combination of those advantages. The results revealed that the alkalinity of sinter could be accurately predicted using this model by reference to small sample and information. The experimental results showed that the grey support vector machine model was effective and practical owing to the advantages of high precision, less samples required, and simple calculation.

关键词： alkalinity sinter grey least squares support vector machine prediction sintering process grey model

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Real-time operation guide system for sintering process with artificial intelligence

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Journal of Central South University of Technology 2005年第5期12卷 531-535页

作者：范晓慧陈许玲姜涛李桃 School of Resources processing and Bioengineering Central South University Changsha 410083 China

In order to optimize the sintering process, a real-time operation guide system with artificial intelligence was developed, mainly including the data acquisition online subsystem, the sinter chemical composition controller, the sintering process state controller, and the abnormal conditions diagnosis subsystem. Knowledge base of the sintering process controlling was constructed, and inference engine of the system was established. Sinter chemical compositions were controlled by the strategies of self-adaptive prediction, internal optimization and center on basicity. And the state of sintering was stabilized centering on permeability. In order to meet the needs of process change and make the system clear, the system has learning ability and explanation function. The software of the system was developed in Visual C++ programming language. The application of the system shows that the hitting accuracy of sinter compositions and burning through point prediction are more than 85%; the first-grade rate of sinter chemical composition, stability rate of burning through point and stability rate of sintering process are increased by 3%, 9% and 4%, respectively.

关键词： sintering process process control artificial intelligence

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Research and industrial testing of dioxin emission reduction technology in the sintering process

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Baosteel Technical Research 2021年第3期15卷 1-8页

作者： YU Yongmei Research Institute Baoshan Iron&Steel Co.Ltd.Shanghai 201999China

Based on an analysis of the chlorine elements in each component of the sintering mixture,industrial tests of the use of dioxin reduction techniques in the sintering process were found to reduce the chlorine sources and inhibit the formation of *** dioxin reduction effect obtained in the industrial experiment was better than that in the sintering pot experiment,but their patterns were *** urea is used as an inhibitor,the dioxins can be significantly *** a 0.02%ratio of urea was added,a maximum dioxin emission reduction of 79%was *** the chlorine sources also had an obvious dioxin reduction effect,enabling a 69.49%*** addition,when these two technologies were applied simultaneously,a significant emission reduction rate of 92.23%was *** concentration of dioxins in flue gas dropped to 0.2421 ng TEQ/m^(3) before desulfurization,which meets the emission standard for dioxins in the final exhaust gas.

关键词： dioxins flue gas sintering process

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