复杂构造矿床煤质控制的动态模型构建方法

I. Osipova
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It should be noted that in scientific works concerning the quality of mined mineral, the question of the reliability and consistency of incoming geological exploration and mining-technological information and its interpretation was not considered sufficiently thoroughly. Materials and methods of research. In order to solve the existing problem of changing the quality of coal extracted, a multi-level model structure is being created, including coal quality map models, models for presenting knowledge of the coal mining process, а first approximation model for monitoring the quality of coal mined and a probability-graphical model for clarifying existing new knowledge on the uncertainty and unreliability of data presented in the form of the Bayesian network. Research results. On the basis of the created graph representing the change in the quality of coal extracted, the production problem was solved in evaluating the definition and understanding of which indicators have influenced the change in the quality of coal extracted in the form of the Bayesian network and the Algebraic Bayesian network. They are an acyclic graph with the top «Influence of major mining and technological indicators on the quality of coal extracted», which in turn determines the next level of peaks «Numerical estimation (obtained from the previous stage of model construction), allowing to determine the allowable level of extracted coal» and «Quality of mining operations» a set of these representations is fundamental for the complex indicator of quality of extracted coal. In addition to these indicators, vertices are introduced about the existence of certain deviations. As a result, the post-test probability of estimating the influence of the change in the allowable level of coal and the quality of mining operations on the complex indicator of extracted coal is P (Hi | E) = 0.025. Discussion. We can conclude that the posterior probability P (Hi | E) = 0.025 is less than a priori P (Н1) = 0.057 because it includes two basic indicators of express testing and dynamic geometry. This makes it possible to speak about the influence of newly obtained information on the complex indicator of the extracted coal, which appears as the front of exploration and exploitation works to produce real-time mining geometric models of the deposit. These, in turn, serve as the basis for operational planning of coal production in terms of quantity and quality. Conclusion. The study found that the quality of mining operations has a significant impact on the integrated quality of coal produced, which in turn forms the main indicator of dynamic geometry. The study is complicated by the fact that there is a need to establish the regularities of the spatial placement of components and their variability at the spent and developed sites of the deposit. Resume. The article presents the results of research in the form of a method of construction of dynamic model of quality management of mined coal on complex-structural deposits with consideration of existing data and knowledge uncertainties. The application of the Bayesian network has been found to be useful for a more detailed study and refinement of existing new knowledge on the process of quality management of extracted coal under conditions of uncertainty and unreliability. With the help of the Bayesian network, it has been determined that the complex quality of coal produced is influenced by the quality of mining operations and numerical estimates of the acceptable quality level of coal extracted. The study revealed that the quality of mining operations has a significant impact on the complex indicator of the quality of extracted coal, which in turn forms the main indicator of dynamic geometry. The study is complicated by the fact that there is a need to establish the regularities of the spatial placement of components and their variability at the spent and developed sites of the deposit. The results of the research may be useful in creating the next level of dynamic model, namely the development of the Bayesian network for a real-time operational quality management process for coal production, which is one of the components of sustainable development of the coal mining enterprise. Proposals for practical application and direction for future research. Further research and application of the results of the work should be continued towards the creation of the next level of dynamic model for the development of the Bayesian network for the process of operational quality management of hard-to-obtain coal structural coal deposits in real mode. Funding: The work was carried out within the framework of the State Order No. 075-00412-22 PR. Theme 1 (2022-2024). 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In order to solve the existing problem of changing the quality of coal extracted, a multi-level model structure is being created, including coal quality map models, models for presenting knowledge of the coal mining process, а first approximation model for monitoring the quality of coal mined and a probability-graphical model for clarifying existing new knowledge on the uncertainty and unreliability of data presented in the form of the Bayesian network. Research results. On the basis of the created graph representing the change in the quality of coal extracted, the production problem was solved in evaluating the definition and understanding of which indicators have influenced the change in the quality of coal extracted in the form of the Bayesian network and the Algebraic Bayesian network. They are an acyclic graph with the top «Influence of major mining and technological indicators on the quality of coal extracted», which in turn determines the next level of peaks «Numerical estimation (obtained from the previous stage of model construction), allowing to determine the allowable level of extracted coal» and «Quality of mining operations» a set of these representations is fundamental for the complex indicator of quality of extracted coal. In addition to these indicators, vertices are introduced about the existence of certain deviations. As a result, the post-test probability of estimating the influence of the change in the allowable level of coal and the quality of mining operations on the complex indicator of extracted coal is P (Hi | E) = 0.025. Discussion. We can conclude that the posterior probability P (Hi | E) = 0.025 is less than a priori P (Н1) = 0.057 because it includes two basic indicators of express testing and dynamic geometry. This makes it possible to speak about the influence of newly obtained information on the complex indicator of the extracted coal, which appears as the front of exploration and exploitation works to produce real-time mining geometric models of the deposit. These, in turn, serve as the basis for operational planning of coal production in terms of quantity and quality. Conclusion. The study found that the quality of mining operations has a significant impact on the integrated quality of coal produced, which in turn forms the main indicator of dynamic geometry. The study is complicated by the fact that there is a need to establish the regularities of the spatial placement of components and their variability at the spent and developed sites of the deposit. Resume. 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引用次数: 0

摘要

介绍煤矿的可持续发展和煤炭生产的质量控制密不可分。影响煤质的主要因素有三个:地质因素、技术因素和工业因素。这些因素的影响过程各不相同:现场质量指标的平均值通常从勘探数据中得知,在采煤过程中,质量值可能会发生变化。在固体矿床复杂开发战略方面,保持所需的煤炭质量生产平衡是煤矿企业的当务之急。应该指出的是,在有关所开采矿物质量的科学著作中,没有充分彻底地考虑传入的地质勘探和采矿技术信息及其解释的可靠性和一致性问题。研究材料和方法。为了解决现有的煤炭开采质量变化问题,正在创建一个多层次的模型结构,包括煤炭质量图模型、用于表示煤炭开采过程知识的模型、,а用于监测开采煤炭质量的第一近似模型和用于澄清以贝叶斯网络形式呈现的关于数据的不确定性和不可靠性的现有新知识的概率图形模型。研究结果。在所创建的表示提取煤炭质量变化的图的基础上,以贝叶斯网络和代数贝叶斯网络的形式评估和理解哪些指标影响了提取煤炭质量的变化,从而解决了生产问题。它们是一个非循环图,顶部为“主要采矿和技术指标对开采煤炭质量的影响”,这反过来决定了下一个峰值水平“数值估计(从模型构建的前一阶段获得),允许确定开采煤炭的允许水平»和《采矿作业质量》这些表示的集合是开采煤炭质量复杂指标的基础。除了这些指标外,顶点还引入了关于某些偏差的存在性。因此,估计煤的允许水平和采矿作业质量的变化对提取煤的复杂指标的影响的测试后概率为P(Hi|E)=0.025。讨论我们可以得出结论,后验概率P(Hi|E)=0.025小于先验概率P(Н1)=0.057,因为它包括表达测试和动态几何这两个基本指标。这使得可以谈论新获得的信息对提取煤的复杂指标的影响,该指标作为勘探和开发工作的前沿出现,以生成矿床的实时开采几何模型。这些反过来又成为煤炭生产在数量和质量方面进行运营规划的基础。结论研究发现,采矿作业质量对所产煤炭的综合质量有重大影响,而综合质量又构成了动态几何的主要指标。这项研究由于需要确定矿床废弃和开发地点的成分空间分布规律及其可变性而变得复杂。简历本文以一种在考虑现有数据和知识不确定性的情况下,构建复杂结构矿床开采煤炭质量管理动态模型的方法的形式,介绍了研究结果。贝叶斯网络的应用已被发现有助于更详细地研究和完善关于在不确定性和不可靠性条件下提取煤的质量管理过程的现有新知识。在贝叶斯网络的帮助下,已经确定所生产的煤炭的复杂质量受到采矿作业质量和所提取煤炭的可接受质量水平的数值估计的影响。研究表明,采矿作业质量对复杂的采出煤质量指标有显著影响,而采出煤又构成了动态几何的主要指标。这项研究由于需要确定矿床废弃和开发地点的成分空间分布规律及其可变性而变得复杂。研究结果可能有助于创建下一级的动态模型,即开发用于煤炭生产实时运营质量管理过程的贝叶斯网络,这是煤矿企业可持续发展的组成部分之一。对实际应用和未来研究方向的建议。
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Dynamic model construction method for coal quality control in complex-structural deposits
Introduction. Sustainable development of the coal mine is inextricably linked to quality control of the coal produced. Three main factors influence coal quality: geological, technological and industrial. The process of these factors influencing is varied: mean values of field quality indicators are generally known from exploration data, and during coal mining quality values may change. Keeping the required production balance in terms of the quality of coal produced is an immediate task of the coal-mining enterprise in terms of the strategy of complex development of solid mineral deposits. It should be noted that in scientific works concerning the quality of mined mineral, the question of the reliability and consistency of incoming geological exploration and mining-technological information and its interpretation was not considered sufficiently thoroughly. Materials and methods of research. In order to solve the existing problem of changing the quality of coal extracted, a multi-level model structure is being created, including coal quality map models, models for presenting knowledge of the coal mining process, а first approximation model for monitoring the quality of coal mined and a probability-graphical model for clarifying existing new knowledge on the uncertainty and unreliability of data presented in the form of the Bayesian network. Research results. On the basis of the created graph representing the change in the quality of coal extracted, the production problem was solved in evaluating the definition and understanding of which indicators have influenced the change in the quality of coal extracted in the form of the Bayesian network and the Algebraic Bayesian network. They are an acyclic graph with the top «Influence of major mining and technological indicators on the quality of coal extracted», which in turn determines the next level of peaks «Numerical estimation (obtained from the previous stage of model construction), allowing to determine the allowable level of extracted coal» and «Quality of mining operations» a set of these representations is fundamental for the complex indicator of quality of extracted coal. In addition to these indicators, vertices are introduced about the existence of certain deviations. As a result, the post-test probability of estimating the influence of the change in the allowable level of coal and the quality of mining operations on the complex indicator of extracted coal is P (Hi | E) = 0.025. Discussion. We can conclude that the posterior probability P (Hi | E) = 0.025 is less than a priori P (Н1) = 0.057 because it includes two basic indicators of express testing and dynamic geometry. This makes it possible to speak about the influence of newly obtained information on the complex indicator of the extracted coal, which appears as the front of exploration and exploitation works to produce real-time mining geometric models of the deposit. These, in turn, serve as the basis for operational planning of coal production in terms of quantity and quality. Conclusion. The study found that the quality of mining operations has a significant impact on the integrated quality of coal produced, which in turn forms the main indicator of dynamic geometry. The study is complicated by the fact that there is a need to establish the regularities of the spatial placement of components and their variability at the spent and developed sites of the deposit. Resume. The article presents the results of research in the form of a method of construction of dynamic model of quality management of mined coal on complex-structural deposits with consideration of existing data and knowledge uncertainties. The application of the Bayesian network has been found to be useful for a more detailed study and refinement of existing new knowledge on the process of quality management of extracted coal under conditions of uncertainty and unreliability. With the help of the Bayesian network, it has been determined that the complex quality of coal produced is influenced by the quality of mining operations and numerical estimates of the acceptable quality level of coal extracted. The study revealed that the quality of mining operations has a significant impact on the complex indicator of the quality of extracted coal, which in turn forms the main indicator of dynamic geometry. The study is complicated by the fact that there is a need to establish the regularities of the spatial placement of components and their variability at the spent and developed sites of the deposit. The results of the research may be useful in creating the next level of dynamic model, namely the development of the Bayesian network for a real-time operational quality management process for coal production, which is one of the components of sustainable development of the coal mining enterprise. Proposals for practical application and direction for future research. Further research and application of the results of the work should be continued towards the creation of the next level of dynamic model for the development of the Bayesian network for the process of operational quality management of hard-to-obtain coal structural coal deposits in real mode. Funding: The work was carried out within the framework of the State Order No. 075-00412-22 PR. Theme 1 (2022-2024). Methodological foundations of the strategy for the integrated development of reserves of solid mineral deposits in the dynamics of the development of mining systems (FUWE-2022-0005), reg. №1021062010531-8-1.5.1.
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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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