Volume 50 Issue 1
Jan.  2024
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SHANG Weidong, WANG Haili, ZHANG Xiaoxia, et al. A coal mine data acquisition, fusion and sharing system based on object model[J]. Journal of Mine Automation,2024,50(1):17-24, 34.  doi: 10.13272/j.issn.1671-251x.2023070047
Citation: SHANG Weidong, WANG Haili, ZHANG Xiaoxia, et al. A coal mine data acquisition, fusion and sharing system based on object model[J]. Journal of Mine Automation,2024,50(1):17-24, 34.  doi: 10.13272/j.issn.1671-251x.2023070047

A coal mine data acquisition, fusion and sharing system based on object model

doi: 10.13272/j.issn.1671-251x.2023070047
  • Received Date: 2023-07-13
  • Rev Recd Date: 2024-01-20
  • Available Online: 2024-01-31
  • 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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