含铁石英岩富集技术指标的预测评价

R. Ismagilov, E. Chanturiya, D. Shekhirev
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Using the example of the material of the over-latticed product of wet thin screening, we propose a methodological approach and develop an algorithm for preliminary evaluation of the possibility of obtaining magnetite concentrates of improved quality from iron ore concentrates of the MGOC and substantiate the maximum possible technological indicators of the process of enrichment. Research methodology. Fritch’s Analizette 22 laser analyzer, ECLIPSE LV100-POL polarizing microscope, SMZ-1500 optical stereomicroscope equipped with DS-5M-L1 digital micro-photographic system and MLA 650 (FEI Company) automated mineralogical analysis tool complex was used to study. The data array was processed using standard MLA software, as well as personal algorithms, in an Excel environment, taking into account expert knowledge on enrichment technology. Amines were used for the reverse flotation of the crushed super lattice product. The content of elements in the samples was determined by X-ray fluorescence analysis. Research results. A methodological approach to the predictive assessment of technological indicators of ore enrichment is proposed, which allows, based on the study of a statistically representative number of particles of the source material and expert technological knowledge, to calculate the mineral, elemental composition, the maximum possible quality and extraction of valuable components and impurities into the concentrate. On the example of the over-lattice product of fine screening of an ordinary concentrate of magnetic separation of nonoxidized ferruginous quartzites of the Mikhailovsky GOK named after A.V. Varichev developed an algorithm for predictive evaluation of technological indicators enrichment, which consists in processing information about the mass fraction of each particle among the statistically reliable number of counted particles, its equivalent diameter, the mass fraction of all minerals and elements included in the particle, as well as the fraction of the particle surface represented by each of the minerals and a number of other parameters using standard MLA software, as well as its own algorithms, in the Excel environment, taking into account expert knowledge on enrichment technology. Additional processing of information in the Excel environment involves ranking and sampling of particles by quality, as well as sampling by size, mineral and elemental composition. The ranking is carried out according to three options: in descending order of the content of magnetite, the total content of magnetite, hematite, and carbonates, as well as the total content of magnetite, hematite, carbonates and aegirine. The ordered database obtained as a result of particle ranking is used for virtual accumulation of the calculated concentrate. Virtual accumulation was carried out by attaching to the calculated concentrate of all particles sequentially, one by one, from an ordered database: from the first with the maximum quality to the last with the minimum. Since for each particle its yield (mass fraction) of all the particles in the database is known, as well as the mass fractions of elements and minerals, the yield, content and extraction of all components can also be calculated for the accumulated concentrate as the particles are added. Thus, as a result, the enrichment characteristics can be established, linking the content of the component selected as a criterion for the quality of particles with its extraction into the concentrate, as well as with the yield of the concentrate, the content and extraction of the remaining controlled components into it. The results of the calculations make it possible to build the enrichment curves of the material by minerals and elements. Resume. The possibility of obtaining from a thin-screen product of fine screening of ordinary magnetic separation concentrate the MGOK, magnetite concentrates the quality of which meets the requirements of the production of DRI pellets has been established: the maximum theoretically achievable quality of magnetite magnetite concentrate is 71.90 % Fe, 1.04 % SiO2, 0.019 % K2O when the concentrate is 53.7 % and Fe is extracted into it. 60,00 %. Taking into account mechanical losses and a variant of the mineral composition of the final magnetite concentrate: in the absence of aegirine, the maximum theoretically achievable quality will be 70.94 % of total iron, silica – up to 1.50 %, potassium oxide – 0.04 %, sodium oxide is absent. At the same time, iron extraction is reduced to 60.58 %. If aegirine passes into the concentrate, the maximum achievable quality of the concentrate is 70.88 % iron, 1.52 % silica, 0.02 % potassium oxide and 0.23 % sodium oxide. Flotation experiments in laboratory conditions have confirmed the validity of the proposed methodological approach to the predictive assessment of mineral enrichment. Magnetite concentrates (chamber products of reverse flotation with amines) were obtained, containing silica (1.3–1.5 %) and total iron (70.3–70.5 %) with the extraction of total iron 53-60 %. Conclusion. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. Varichev. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. Varichev.","PeriodicalId":37608,"journal":{"name":"Sustainable Development of Mountain Territories","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prognostical assessment of technological indicators of ferruginous quartzites enrichment\",\"authors\":\"R. Ismagilov, E. Chanturiya, D. 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Using the example of the material of the over-latticed product of wet thin screening, we propose a methodological approach and develop an algorithm for preliminary evaluation of the possibility of obtaining magnetite concentrates of improved quality from iron ore concentrates of the MGOC and substantiate the maximum possible technological indicators of the process of enrichment. Research methodology. Fritch’s Analizette 22 laser analyzer, ECLIPSE LV100-POL polarizing microscope, SMZ-1500 optical stereomicroscope equipped with DS-5M-L1 digital micro-photographic system and MLA 650 (FEI Company) automated mineralogical analysis tool complex was used to study. The data array was processed using standard MLA software, as well as personal algorithms, in an Excel environment, taking into account expert knowledge on enrichment technology. Amines were used for the reverse flotation of the crushed super lattice product. The content of elements in the samples was determined by X-ray fluorescence analysis. Research results. A methodological approach to the predictive assessment of technological indicators of ore enrichment is proposed, which allows, based on the study of a statistically representative number of particles of the source material and expert technological knowledge, to calculate the mineral, elemental composition, the maximum possible quality and extraction of valuable components and impurities into the concentrate. On the example of the over-lattice product of fine screening of an ordinary concentrate of magnetic separation of nonoxidized ferruginous quartzites of the Mikhailovsky GOK named after A.V. Varichev developed an algorithm for predictive evaluation of technological indicators enrichment, which consists in processing information about the mass fraction of each particle among the statistically reliable number of counted particles, its equivalent diameter, the mass fraction of all minerals and elements included in the particle, as well as the fraction of the particle surface represented by each of the minerals and a number of other parameters using standard MLA software, as well as its own algorithms, in the Excel environment, taking into account expert knowledge on enrichment technology. Additional processing of information in the Excel environment involves ranking and sampling of particles by quality, as well as sampling by size, mineral and elemental composition. The ranking is carried out according to three options: in descending order of the content of magnetite, the total content of magnetite, hematite, and carbonates, as well as the total content of magnetite, hematite, carbonates and aegirine. The ordered database obtained as a result of particle ranking is used for virtual accumulation of the calculated concentrate. Virtual accumulation was carried out by attaching to the calculated concentrate of all particles sequentially, one by one, from an ordered database: from the first with the maximum quality to the last with the minimum. Since for each particle its yield (mass fraction) of all the particles in the database is known, as well as the mass fractions of elements and minerals, the yield, content and extraction of all components can also be calculated for the accumulated concentrate as the particles are added. Thus, as a result, the enrichment characteristics can be established, linking the content of the component selected as a criterion for the quality of particles with its extraction into the concentrate, as well as with the yield of the concentrate, the content and extraction of the remaining controlled components into it. The results of the calculations make it possible to build the enrichment curves of the material by minerals and elements. Resume. The possibility of obtaining from a thin-screen product of fine screening of ordinary magnetic separation concentrate the MGOK, magnetite concentrates the quality of which meets the requirements of the production of DRI pellets has been established: the maximum theoretically achievable quality of magnetite magnetite concentrate is 71.90 % Fe, 1.04 % SiO2, 0.019 % K2O when the concentrate is 53.7 % and Fe is extracted into it. 60,00 %. Taking into account mechanical losses and a variant of the mineral composition of the final magnetite concentrate: in the absence of aegirine, the maximum theoretically achievable quality will be 70.94 % of total iron, silica – up to 1.50 %, potassium oxide – 0.04 %, sodium oxide is absent. At the same time, iron extraction is reduced to 60.58 %. If aegirine passes into the concentrate, the maximum achievable quality of the concentrate is 70.88 % iron, 1.52 % silica, 0.02 % potassium oxide and 0.23 % sodium oxide. Flotation experiments in laboratory conditions have confirmed the validity of the proposed methodological approach to the predictive assessment of mineral enrichment. Magnetite concentrates (chamber products of reverse flotation with amines) were obtained, containing silica (1.3–1.5 %) and total iron (70.3–70.5 %) with the extraction of total iron 53-60 %. Conclusion. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. Varichev. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. 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引用次数: 0

摘要

ntroduction。在开发矿物原料浓缩技术时,关于其物质成分的可靠信息和对所获得数据的合格技术解释是重要的,这使我们能够预先评估获得所需质量的浓缩产品的可能性。生产金属化球团(DRI)和热压块铁(HBI)的原料质量对铁、二氧化硅和其他杂质的含量要求很高。对于以A.V. Varicheva (MGOKa)命名的Mikhailovsky GOK (MGOKa)来说,首要任务是开发一种分离高质量磁铁矿精矿的技术,减少杂质含量,生产DRI球团。工作的目的。以湿式薄筛过晶格产品为例,提出了一种方法方法,并开发了一种算法,用于初步评估从MGOC铁矿精矿中获得高质量磁铁矿精矿的可能性,并证实了富集过程的最大可能技术指标。研究方法。采用美国Fritch公司的Analizette 22激光分析仪、ECLIPSE LV100-POL偏光显微镜、配备DS-5M-L1数码显微照相系统的SMZ-1500光学立体显微镜和FEI公司的MLA 650自动化矿物分析工具复合物进行研究。考虑到富集技术方面的专家知识,在Excel环境下,使用标准的MLA软件以及个人算法处理数据阵列。用胺对粉碎后的超晶格产物进行反浮选。用x射线荧光法测定样品中元素的含量。研究的结果。提出了一种预测评价矿石富集技术指标的方法学方法,根据对源材料中具有统计代表性的颗粒数量和专家技术知识的研究,计算矿物、元素组成、可能的最高质量以及从精矿中提取有价值的成分和杂质。以米哈伊洛夫斯基GOK(以A.V. Varichev命名)的非氧化含铁石英岩的普通磁选精矿精细筛选的过晶格积为例,开发了一种技术指标富集预测评估算法,该算法包括处理有关统计可靠计数颗粒中每个颗粒的质量分数的信息,其等效直径,在Excel环境中,考虑到富集技术的专家知识,使用标准MLA软件以及自己的算法,计算颗粒中包含的所有矿物和元素的质量分数,以及每种矿物所代表的颗粒表面的分数和许多其他参数。在Excel环境中对信息的额外处理包括按质量对颗粒进行排序和采样,以及按大小、矿物和元素组成进行采样。按照磁铁矿含量由高到低、磁铁矿、赤铁矿、碳酸盐总含量、磁铁矿、赤铁矿、碳酸盐总含量、铁铁矿、赤铁矿、碳酸盐总含量三种方案进行排序。由颗粒排序得到的有序数据库用于计算精矿的虚拟堆积。从一个有序的数据库中,从质量最高的第一个到质量最低的最后一个,逐个附加到计算出的所有颗粒的浓缩物上,进行虚拟积累。由于对于每个颗粒,数据库中所有颗粒的产率(质量分数)以及元素和矿物的质量分数都是已知的,因此随着颗粒的加入,也可以计算出累积精矿中所有组分的产率、含量和提取率。因此,可以建立富集特征,将选定的作为颗粒质量标准的组分的含量与其萃取到浓缩物中,以及浓缩物的得率、剩余受控组分的含量和萃取到浓缩物中联系起来。计算结果为建立该物质的矿物和元素富集曲线提供了可能。重新开始确定了从普通磁选精矿细筛薄筛产品中获得MGOK磁铁矿精矿的可能性,该磁铁矿精矿的质量满足DRI球团生产的要求:当磁铁矿精矿质量为53.7%并将铁提取其中时,磁铁矿精矿的最大理论可达质量为71.90% Fe、1.04% SiO2、0.019% K2O。60岁的00%。 考虑到机械损失和最终磁铁矿精矿矿物组成的变化:在不含铝的情况下,理论上可达到的最大质量将是总铁的70.94%,二氧化硅-高达1.50%,氧化钾- 0.04%,氧化钠不存在。同时,铁的提取率降至60.58%。如果将铁碱带入精矿,则精矿的最高可达质量为铁70.88%、二氧化硅1.52%、氧化钾0.02%和氧化钠0.23%。实验室条件下的浮选实验证实了该方法对矿物富集预测评价的有效性。得到磁铁矿精矿(胺反浮选室产物),含二氧化硅(1.3 ~ 1.5%)、总铁(70.3 ~ 70.5%),总铁提取率为53 ~ 60%。结论。所进行的研究结果建议在以A.V.瓦里切夫命名的米哈伊洛夫斯基GOK开发普通磁铁矿精矿额外富集技术的实际实施中。所进行的研究结果建议在以A.V.瓦里切夫命名的米哈伊洛夫斯基GOK开发普通磁铁矿精矿额外富集技术的实际实施中。
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Prognostical assessment of technological indicators of ferruginous quartzites enrichment
ntroduction. When developing a technology for the enrichment of mineral raw materials, reliable information about its material composition and a qualified technological interpretation of the data obtained is important which allows us to pre-evaluate the possibility of obtaining enrichment products of the required quality. The quality of raw materials to produce metallized pellets (DRI) and hot-briquetted iron (HBI) has high requirements for the content of iron, silica, and other impurities. For Mikhailovsky GOK named after A.V. Varicheva (MGOKa) the priority task is to develop a technology for the isolation of high-quality magnetite concentrates with a reduced content of impurities to produce DRI pellets. The purpose of the work. Using the example of the material of the over-latticed product of wet thin screening, we propose a methodological approach and develop an algorithm for preliminary evaluation of the possibility of obtaining magnetite concentrates of improved quality from iron ore concentrates of the MGOC and substantiate the maximum possible technological indicators of the process of enrichment. Research methodology. Fritch’s Analizette 22 laser analyzer, ECLIPSE LV100-POL polarizing microscope, SMZ-1500 optical stereomicroscope equipped with DS-5M-L1 digital micro-photographic system and MLA 650 (FEI Company) automated mineralogical analysis tool complex was used to study. The data array was processed using standard MLA software, as well as personal algorithms, in an Excel environment, taking into account expert knowledge on enrichment technology. Amines were used for the reverse flotation of the crushed super lattice product. The content of elements in the samples was determined by X-ray fluorescence analysis. Research results. A methodological approach to the predictive assessment of technological indicators of ore enrichment is proposed, which allows, based on the study of a statistically representative number of particles of the source material and expert technological knowledge, to calculate the mineral, elemental composition, the maximum possible quality and extraction of valuable components and impurities into the concentrate. On the example of the over-lattice product of fine screening of an ordinary concentrate of magnetic separation of nonoxidized ferruginous quartzites of the Mikhailovsky GOK named after A.V. Varichev developed an algorithm for predictive evaluation of technological indicators enrichment, which consists in processing information about the mass fraction of each particle among the statistically reliable number of counted particles, its equivalent diameter, the mass fraction of all minerals and elements included in the particle, as well as the fraction of the particle surface represented by each of the minerals and a number of other parameters using standard MLA software, as well as its own algorithms, in the Excel environment, taking into account expert knowledge on enrichment technology. Additional processing of information in the Excel environment involves ranking and sampling of particles by quality, as well as sampling by size, mineral and elemental composition. The ranking is carried out according to three options: in descending order of the content of magnetite, the total content of magnetite, hematite, and carbonates, as well as the total content of magnetite, hematite, carbonates and aegirine. The ordered database obtained as a result of particle ranking is used for virtual accumulation of the calculated concentrate. Virtual accumulation was carried out by attaching to the calculated concentrate of all particles sequentially, one by one, from an ordered database: from the first with the maximum quality to the last with the minimum. Since for each particle its yield (mass fraction) of all the particles in the database is known, as well as the mass fractions of elements and minerals, the yield, content and extraction of all components can also be calculated for the accumulated concentrate as the particles are added. Thus, as a result, the enrichment characteristics can be established, linking the content of the component selected as a criterion for the quality of particles with its extraction into the concentrate, as well as with the yield of the concentrate, the content and extraction of the remaining controlled components into it. The results of the calculations make it possible to build the enrichment curves of the material by minerals and elements. Resume. The possibility of obtaining from a thin-screen product of fine screening of ordinary magnetic separation concentrate the MGOK, magnetite concentrates the quality of which meets the requirements of the production of DRI pellets has been established: the maximum theoretically achievable quality of magnetite magnetite concentrate is 71.90 % Fe, 1.04 % SiO2, 0.019 % K2O when the concentrate is 53.7 % and Fe is extracted into it. 60,00 %. Taking into account mechanical losses and a variant of the mineral composition of the final magnetite concentrate: in the absence of aegirine, the maximum theoretically achievable quality will be 70.94 % of total iron, silica – up to 1.50 %, potassium oxide – 0.04 %, sodium oxide is absent. At the same time, iron extraction is reduced to 60.58 %. If aegirine passes into the concentrate, the maximum achievable quality of the concentrate is 70.88 % iron, 1.52 % silica, 0.02 % potassium oxide and 0.23 % sodium oxide. Flotation experiments in laboratory conditions have confirmed the validity of the proposed methodological approach to the predictive assessment of mineral enrichment. Magnetite concentrates (chamber products of reverse flotation with amines) were obtained, containing silica (1.3–1.5 %) and total iron (70.3–70.5 %) with the extraction of total iron 53-60 %. Conclusion. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. Varichev. The results of the conducted research are recommended for practical implementation in the development of the technology of additional enrichment of ordinary magnetite concentrate at the Mikhailovsky GOK named after A.V. Varichev.
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来源期刊
Sustainable Development of Mountain Territories
Sustainable Development of Mountain Territories Social Sciences-Sociology and Political Science
CiteScore
2.40
自引率
0.00%
发文量
36
期刊介绍: International scientific journal "Sustainable development of mountain territories" covers fundamental and applied regional, national and international research and provides a platform to publish original full papers and related reviews in the following areas: engineering science and Earth science in the field of sustainable development of mountain territories. Main objectives of international scientific journal "Sustainable development of mountain territories" are: raising the level of professional scientific workers, teachers of higher educational institutions and scientific organizations; presentation of research results in the field of sustainable development of mountain areas on the technical aspects and Earth sciences, informing readers about the results of Russian and international scientific forums; improved review and editing of the articles submitted for publication; ensuring wide dissemination for the published articles in the international academic environment; encouraging dissemination and indexing of scientific works in various foreign key citation databases.
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