A coal mine data acquisition, fusion and sharing system based on object model
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摘要: 针对目前煤矿数据采集、融合与共享存在的设备属性缺乏标准化且语义不统一、数据采集规约无法跨操作系统、数据访问实时性差、数据共享效率低等问题，设计了一种基于对象模型的煤矿数据采集融合共享系统。在基于位号的煤矿数据编码标准的基础上设计设备对象模型，克服了设备属性缺少标准化和设备属性语义不统一的问题；采用工业规约采集、Restful API问答式采集和文件数据采集等数据接入方式，可支持国产化操作系统，提供了方便的报文监视工具，能够准确判断通信异常原因；通过设备对象模型映射实现数据融合，引入数据治理机制确保数据的准确性和一致性，以对象模型的形式存储数据来节省存储空间、提高存储效率；将所有设备对象数据存储到一张表中，对象化的数据共享接口可简化成实时数据共享接口和历史数据共享接口，减少了冗余接口，从而降低了数据访问次数。应用结果表明，该系统在对设备数据标准化后降低了数据使用过程中语义解析的难度，同时提高了数据的计算、存储和访问性能，为大数据分析提供了保障。Abstract: In current coal mine data acquisition, fusion, and sharing, there are problems of lack of standardization and semantic inconsistency in device attributes, inability to cross operating systems in data acquisition protocols, poor real-time data access, and low data sharing efficiency. In order to solve the above problems, a coal mine data acquisition, fusion, and sharing system based on object model is designed. On the basis of the coding standard for coal mine data based on tag numbers, a device object model is designed to overcome the problems of lack of standardization of device attributes and semantic inconsistency in device attributes. By using industrial protocol acquisition, Restful API Q&A acquisition, and file data acquisition methods for data access, it can support domestic operating systems and provide convenient message monitoring tools to accurately determine the cause of communication abnormalities. The model implements data fusion through device object model mapping, introduces data governance mechanisms to ensure data accuracy and consistency, and stores data in the form of object models to save storage space and improve storage efficiency. The model stores all device object data in one table. The object-oriented data sharing interface can be simplified into real-time data sharing interface and historical data sharing interface, reducing redundant interfaces and thus reducing data access times. The application results show that the system reduces the difficulty of semantic parsing during data usage after standardizing device data. The system improves the performance of data computation, storage, and access, providing guarantees for big data analysis.
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Key words:
- data acquisition /
- data fusion /
- data sharing /
- object model /
- data encoding /
- data governance /
- data storage
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图 1 基于对象模型的煤矿数据采集融合共享系统架构
Figure 1. Architecture of coal mine data acquisition, fusion and sharing system based on object model
表 1 数据计算性能对比
Table 1. Comparison of data calculation performance
计算方式 准确率/% 每10万条数据计算用时/s 数据存储前计算 90 1 数据使用时计算 87 5 
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表 2 数据存储性能对比
Table 2. Comparison of data storage performance
数据库 松散数据存储速率/（kbit·s−1） 对象数据存储速率/（kbit·s−1） Redis 200 2 000 ClickHouse 100 5 000
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表 3 数据查询性能对比
Table 3. Comparison of data query performance
数据库 松散数据查询速率/（kbit·s−1） 对象数据查询速率/（kbit·s−1） Redis 1 000 4 000 ClickHouse 100 1 000
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