Analysis of methods to prepare and transform information entering data repositories for effective management of the mining system

V.N. Zakharov, D. Klebanov, M.A. Makeev, D.N. Radchenko
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Abstract

The article assesses the existing methods of data collection and processing in the industry and proposes an alternative option of data processing to manage mining engineering systems at various stages of their operation. It is demonstrated that the formed volume of information that comes with different frequency rates and requires dedicated processing, structuring and analysis methods forms a system of big data and serves to enhance the efficiency of implementing geotechnical processes. A possible unified structure of data acquisition from digital sources of mining engineering system is presented. An analysis is provided of possible methods to process data for analytical purposes and for searching implicit dependencies and solving problems of predictive analytics. Tools for data collection and storage are proposed to create a unified system of big data analysis for management of mining engineering systems. It is stated that in order to create a unified analytical system for collection of digital data from a mining system, it is necessary to use standard industrial protocols for data collection and storage, for instance MQTT, used as an industry standard in the Industrial Internet of Things (IIoT) systems in accordance with requirements of ISO/ IEC 20922:2016. Storage requires the use of a conventional queue broker architecture, as well as a tool for working with the time series which is required to apply machine learning and big data methods. The approach to data classification in terms of the data acquisition speed proposed in the article makes it possible to standardize the data handling principles. Since the volume of transmitted data does not depend on the frequency of acquiring information from a digital source, it is proposed to transmit all the generated data from a digital source for subsequent search of implicit dependencies between the data. It is noted that application of specific methods and algorithms to analyze data of a mining system depends primarily on the task set which is often formed as a hypothesis to be tested by identifying implicit dependencies between different data sources. In order to improve the efficiency of managing a mining system at all the stages of field development, it is proposed to apply the ELT approach, which can be an important advantage in terms of controlling the technological processes of the mining system in the future.
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分析准备和转换进入数据储存库的信息的方法,以便有效管理采矿系统
文章对该行业现有的数据收集和处理方法进行了评估,并提出了在采矿工程系统运行的各个阶段对其进行管理的数据处理替代方案。事实证明,形成的信息量具有不同的频率,需要专门的处理、结构化和分析方法,这就形成了一个大数据系统,有助于提高岩土工程流程的实施效率。本文介绍了从采矿工程系统数字源获取数据的统一结构。分析了为分析目的、搜索隐含依赖关系和解决预测分析问题而处理数据的可行方法。提出了收集和存储数据的工具,以便为采矿工程系统的管理创建统一的大数据分析系统。报告指出,为了创建一个统一的分析系统来收集采矿系统的数字数据,有必要使用标准的工业协议来收集和存储数据,例如根据 ISO/ IEC 20922:2016 的要求在工业物联网(IIoT)系统中作为工业标准使用的 MQTT。存储需要使用传统的队列代理架构,以及应用机器学习和大数据方法所需的时间序列处理工具。文章中提出的根据数据采集速度进行数据分类的方法使数据处理原则标准化成为可能。由于传输的数据量并不取决于从数字源获取信息的频率,因此建议传输从数字源生成的所有数据,以便随后搜索数据之间的隐含依赖关系。需要指出的是,应用特定的方法和算法来分析挖掘系统的数据主要取决于任务集,而任务集通常是通过识别不同数据源之间的隐含依赖关系而形成的假设。为了在矿场开发的各个阶段提高采矿系统的管理效率,建议采用 ELT 方法,这对今后控制采矿系统的技术流程具有重要优势。
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