梅山焦炭质量预测模型的研究

结合炼焦配煤生产数据,从单种煤指标的加和性分析开始,利用回归方法建立适合梅山自身特点的焦炭灰分、硫分、M_(40)、M_(10)、CRI和CSR的预测模型,并对模型进行了检验。结果表明,所建立焦炭质量预测模型能够预测焦炭质量,优化炼焦配煤配比,满足生产需要,为稳定焦炭质量和降低配煤成本创造了条件。     

韶钢焦炭质量预测模型的研究

基于韶钢2016年的焦炭质量数据,利用回归法进行数据分析与处理,建立焦炭质量预测模型,应用于韶钢开发的产销系统,实现了焦炭质量预测自动化,为优化配煤结构、降低配煤成本提供了理论支撑。     

焦炭质量预测方法的应用

以太原煤炭气化(集团)有限责任公司的工业焦炉数据为基础,建立了该公司的焦炭质量预测模型。利用单种煤和配合煤的各种性质指标预测焦炭质量,并指导配煤,以获得稳定的焦炭质量。     

炼焦配煤专家系统的设计及应用

配煤专家系统以焦炭质量预测模型和配煤比优化模型为基础,包含数据收集、数据存储、知识库、推理机等功能模块,对焦炭灰分、硫分、M40、M10、CRI、CSR进行预测,快速计算最佳配煤比。系统得到的焦炭质量指标误差小于6%,能够满足企业生产的要求。     

焦炭机械强度预测模型的研究

焦炭机械强度是焦炭质量的重要指标,建立准确的焦炭机械强度预测模型可保证炼焦生产顺利进行.把支持向量回归机用于焦炭机械强度的预测,详细地分析了不同配煤煤质特性指标及炼焦工艺指标情况下的预测效果,找到了建立预测模型的有效特征参数.基于所选特征参数,当85≤M25≤90,6≤M10≤12时,支持向量机模型的预测准确率高,误差小,相关性强,同时,预测模型的泛化能力强.     

单种煤结焦性能评价与焦炭质量预测

根据11种单种煤的性质,在实验室20kg小焦炉上进行了11种单种煤和8种配煤方案的炼焦实验,并对焦炭进行了筛分组成、冷态强度、焦炭热性质等分析,初步建立了焦炭质量预测模型。实验结果表明:单一的煤质指标与焦炭强度的关系不是很明显,选用煤质多因素指标进行焦炭质量预测,其预测效果较好;单一的煤质指标(Vd、R0max、Ad)与焦炭反应性之间有较好的关系,且焦炭的反应性随反应温度的升高而增大。     

基于GRU神经网络多标签多分类的焦炭质量预测模型

通过关联配合煤中硫、灰分、挥发分的质量分数等主要的煤质指标，利用基于Adma算法为优化器的GRU神经网络模型，不断对模型参数进行调整后，通过sigmoid激活函数判断模型准确率的多标签多分类方法，建立了焦炭质量预测模型。结果表明：当三层GRU网络的隐层神经元数量为(64,64,64);学习率为0.01;样本批次大小为64;样本训练次数为50;丢弃率为0.3时，得到了模型的最优参数，此时模型预测准确率达到97%。采用GRU神经网络多标签多分类焦炭预测模型不仅具有高精度、低损失函数等特点，而且针对小样本配煤数据预测焦炭质量可以达到很好的效果，对实际的配煤炼焦具有一定的参考意义。     

焦炭强度与热性质控制因素分析

在20kg小焦记上进行了11种单种煤和8种配煤方案的炼焦试验,建立了焦炭质量预测模型。结果表明,单一的煤质指标与焦炭强度的关系不明显,多因素指标进行焦炭质量的预测效果较好;焦炭反应性与单一煤质指标中Vd、^—Rmax^0、Ad之间有较好的关系,且随反应温度的升高而增大。     

微观分析技术在优选炼焦煤中的应用

邯钢焦化厂通过煤岩显微组分分析和焦炭光学组织含量分析的研究和应用,和小焦炉试验有机结合,建立了焦炭热强度和焦炭光学组织、焦炭光学组织和煤岩显微组分之间的模型,能够根据煤的显微组分判断所产焦炭的质量,科学地指导配煤炼焦生产,从而达到准确预测焦炭质量,优选炼焦煤种,最大限度地降低配煤炼焦成本的目标。     

基于BP神经网络的焦炭质量预测

分析了配煤炼焦中影响焦炭质量指标的各种因素及传统焦炭质量的预测方法。以天津天铁焦化厂的配合煤及生产焦炭的各项实际数据为基础,在MATLAB环境下,进行了基于BP神经网络对焦炭质量预测的方法研究。实验结果显示:3种网络的误差基本相同,范围在2%～0.05%,以中间层为15个神经元的略好,满足焦炭质量的预测要求。     

在配煤中添加石油焦对焦炭质量的影响

研究了在配煤中添加石油焦对焦炭质量的影响。采取配比为5%的不同粒度的添加方案进行配煤炼焦实验,最佳配煤方案与武钢生产配煤焦炭相比,灰分降低0.57%,硫分增加0.02%,抗碎强度基本不变,耐磨强度M10下降0.95%,反应性降低3.12%,反应后强度提高6.59%。焦炭的X-射线衍射对比测试表明,在配煤中加入石油焦能促进焦炭各向异性的发展。     

Heat recovery stamp charged coke making: An experience in operational excellence

The coal blend quality and process control of coke making technologies is an important lever to produce quality coke with optimal cost. Apart from impacting cost, this improves the CO₂ footprint. This is facilitated by proper selection of coke making technologies and coal/coal blend. Each technology has its own advantage and limitation based on its design criteria. Recently, Tata Steel introduced Asia largest single location 1.6 mtpa of heat recovery coke plant for the first time. This paper briefly described the operational philosophy evolved in heat recovery coke plant to produce desired quality coke at comparatively lower cost through operational excellence. The reduction of imported prime hard coking coal in coal blend up to 30% without affecting coke quality adversly and understanding the operational processes and finally mastering heat recovery coke making technology was also part of this paper.     

A semi-industrial scale study of petroleum coke as an additive in cokemaking

The addition of petroleum coke to a typical industrial coal blend used in the production of metallurgical coke was studied. Cokes were produced at semi-industrial scale at the INCAR coking plant, using petroleum coke of different particle size distribution as an additive. Special attention was paid to changes caused in the textural properties (porosity, pore size distribution, fissures at the interface between metallurgical coke and petroleum coke) which have been found to be responsible for variations in the metallurgical coke quality parameters (e.g., mechanical strength and reactivity towards CO₂). Variation in porosity was found to depend on particle size and the proportion of the additive. The decrease in the microporosity (i.e., pore radius<3.7 nm) of the metallurgical cokes observed when petroleum coke is added to the coal blend, is postulated to be one of the main factors responsible for the decrease in the reactivity of these cokes. The variation of the mechanical strength indices can be explained by the changes in porosity and the quality of the interfaces between petroleum coke and metallurgical coke.     

捣固炼焦值得关注的几个问题

叙述了捣同炼焦配煤与焦炭质量的关系及捣固强度与配煤的关联性.指出:焦炭质量的基础是配煤质量,不会因煤准备和炼焦工艺等有根本性的改变;捣固炼焦可多用低变质程度,高挥发分气煤类的炼焦煤生产出一定质量的焦炭;捣同炼焦配煤适当增加黏结性配煤比例可提高焦炭质量,但用接近顶装焦炉的配煤进行捣固炼焦将丧失其优势并引发问题.捣固焦炉的...     

焦炭热性能的影响因素探讨

通过对梅山焦炭反应性、反应后强度和配煤质量指标进行的试验分析,结果表明:焦炭灰分、配煤挥发分和胶质层最大厚度Y值是影响焦炭热性能的重要因素,而焦炭的冷强度M40和M10与焦炭热性能没有明显的相关关系。     

高硫气肥煤替代肥煤炼焦的研究和应用

对价格较低的高硫气肥煤进行了工业分析、煤质分析、岩相分析和40 kg小焦炉试验,并将其用于配煤炼焦。结果表明,高硫气肥煤部分替代肥煤炼焦是可行的,将其应用到生产实践,焦炭质量得到了保证,同时降低了配合煤成本。     

顶装炼焦改造为捣固炼焦的生产实践

介绍了JN43-80型焦炉由顶装炼焦改为捣固炼焦的改造工程,对比了改造前后炼焦用煤质量指标、配煤煤种和比例、用煤量、焦炭质量指标、化工产品回收率等。顶装炼焦改为捣固炼焦具有减少主焦煤配入量、增加气煤的配入量、提高焦炭产量等优势,通过改造,可使焦化企业降本增效。     

An approach to blast furnace coke quality prediction

Although coke cold drum mechanical strength has historically been the most relevant coke quality parameter, currently coke reactivity and post-reaction strength (CRI/CSR) are the most important parameters used to assess blast-furnace coke quality. Many models of coke quality prediction have been proposed, most of which are based on coal characteristics and limited to the same coal geographic origin, but as yet there is no universally applicable prediction formula. The present work describes a simple model of coke CRI/CSR prediction based on the assumption that the CSR of a coke produced from a blend of coals can be predicted from the CSR obtained from the cokes of the individual coals through the application of the additivity law. The additivity law was also applied to the coke cold mechanical strength indices derived from the Irsid test, which are widely employed by the European coke industry as complementary coke quality indicators.     

煤的岩相分析在配煤炼焦中的应用

煤岩分析法已成为辨别煤质特别是确认混煤情况的重要手段,它在某些方面弥补了工业分析在检验煤质上的一些不足。文中依据镜质组反射率具有加和性的特点,利用单种煤反射率分布图合成配合煤反射率分布图指导炼焦配煤,可以使焦炭质量达到最优。