智能矿山数据质量管理研究及实践
Research and practice of intelligent mine data quality management
韩培强 1胡而已 2叶兰 2冯智愚 1张卫伟3
作者信息
- 1. 陕煤集团神木张家峁矿业有限公司,陕西省榆林市,719300
- 2. 应急管理部信息研究院,北京市 朝阳区,100029
- 3. 应急管理部大数据中心,北京市东城区,100013
- 折叠
摘要
数据作为矿山企业的重要生产力,是数字化、智能化煤矿建设的基础,已快速融入到煤矿生产、运输和安全检查等各环节.从矿山业务场景角度出发,结合煤矿数据特点,阐述了数据质量的定义、维度和数据质量量化管理的概念,从事前预防、事中控制以及事后补救 3 方面介绍了智能矿山数据质量管理策略和技术,从而实现数据质量的全流程控制.以理论指导实践,将相关理论应用于智能矿山的具体业务及生产流程,从顶层设计、组织保障、流程控制以及结果评估等多个方面进行阐述,给出了智能矿山数据质量管理的典型案例.
Abstract
As an important productivity of mining enterprises,Data is the foundation of digital and intelligent coal mine construction and has quickly integrated into various aspects of coal mine production,transportation and safety inspection.Starting from the perspective of mining business scenarios and combining with the characteristics of coal mine data,this paper elaborates on the definition,dimensions and concepts of quantitative management of data quality,introduces intelligent mining data quality management strategies and technologies from three aspects:pre-prevention,in-process control,and post-remediation,so as to achieve full-process control of data quality.Guided by theory,this study applies relevant theories to the specific business and production processes of intelligent mines,elaborates on various aspects such as top-level design,organizational support,process control,and result evaluation,and provides typical cases of data quality management in intelligent mines.
关键词
智能化煤矿/业务场景/数据质量管理/实践应用Key words
intelligent coal mines/business scenarios/data quality management/practical application引用本文复制引用
出版年
2024
NETL
NSTL
万方数据