GE Shirong. Research on concept and system architecture of smart mining workface in coal mine[J]. Journal of Mine Automation, 2020, 46(4): 1-9. DOI: 10.13272/j.issn.1671-251x.2020030070
Citation: GE Shirong. Research on concept and system architecture of smart mining workface in coal mine[J]. Journal of Mine Automation, 2020, 46(4): 1-9. DOI: 10.13272/j.issn.1671-251x.2020030070

Research on concept and system architecture of smart mining workface in coal mine

  • Definition of smart mining workface was put forward as a production system that could independently operate coal mining process without manual interaction. It was pointed out that the smart mining workface depended on intelligent machine, autonomous sensing and controlling and independent operation, which focused on the purpose of unmanned mining. Five intelligent elements of the smart mining workface were introduced, which included the autonomous perception, autonomous decision-making, autonomous control, autonomous collaboration and autonomous interaction. It was suggested that the smart mining workface could be assessed as primary level, intermediate level and advanced level according to different levels of the intelligent elements. In this meaning, the development of smart mining workface would be a gradual process, which closely connected to the building up of the automation, digitalization and internet technology for mining workface. It was predicted that China's coal mines would come to primary smart level in 2025. Some coal mines with better condition would reach up intermediate smart level by 2035 with the equipment capable for autonomous perception and control. The unmanned coal mining was expected to be realized in 2045. The evaluation index for smart mining workface was introduced, and the cobweb map and analytic hierarchy methods were described for evaluating the level of smart mining workface. In order to construct the smart mining workface system, a coupling model was put forward including three intelligent control loops from the coal mining process, equipment operation and coal flow. The model and control loops were beneficial to improving the adaptive performance of coal seam cutting, roof supporting and coal flow transportation. Finally, the smart mining workface architecture with functional, technical and organization dimensions was proposed, which could provide the integration across machines and platforms to form a collaborative and co-managed intelligent mining ecology.
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