Research on technology of key steps of intelligent ventilation in mines
The process steps of intelligent ventilation in mines were proposed, which could make the ventilation system more orderly and controllable. The process of intelligent ventilation in mines was divided into six process sections according to the production process, namely perception monitoring, analysi...
| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Coal Science and Technology
2024-01-01
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| Series: | Meitan kexue jishu |
| Subjects: | |
| Online Access: | http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2023-1987 |
| _version_ | 1827318816417251328 |
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| author | Lang ZHANG Yanqing LIU |
| author_facet | Lang ZHANG Yanqing LIU |
| author_sort | Lang ZHANG |
| collection | DOAJ |
| description | The process steps of intelligent ventilation in mines were proposed, which could make the ventilation system more orderly and controllable. The process of intelligent ventilation in mines was divided into six process sections according to the production process, namely perception monitoring, analysis and diagnosis, intelligent decision-making, scheme approval, remote centralized control and joint control, and execution feedback, which included a total of 24 specific process steps. The input and output elements of each process step and the functional logical relationship between the process steps were clarified. According to the concept of “overall plan of the mine ventilation system+key refinement of the mining air area”, the scheme for implementing the intelligent ventilation process of the entire mine system and two refined intelligent ventilation process application scenarios for the coal mining and excavation working faces were proposed. The intelligent ventilation process steps of the mine were integrated into specific application scenarios. In order to achieve intelligent ventilation application scenarios, the overall architecture of the mine intelligent ventilation system was optimized based on the logical layering concept. The mine intelligent ventilation control platform consisting of hardware driver layer, functional module layer, computing processing layer, data storage layer, and data acquisition layer was planned and designed. The four key process sections of intelligent ventilation involved ten key process sections,which were ventilation perception monitoring, analysis and diagnosis, intelligent decision-making, remote centralized control and joint control. The ten key process steps included monitoring and perception of air volume and wind speed, online monitoring of ventilation resistance, analysis of air volume and pressure in the entire air network, identification and identification of disaster sources, calculation of dynamic air demand in mines, diagnosis of ventilation system faults, decision-making of on-demand air volume control plans, decision-making of emergency air control plans, unmanned remote air control, and unmanned emergency air control. The current technological status of the ten key process steps were summarized and analyzed, and the technical implementation paths for the ten key process steps were proposed. Through iterative upgrades of various intelligent ventilation key technologies, the mine ventilation system was ultimately achieved to be in the stable, reliable, safe, controllable, efficient, energy-saving, and emergency disaster reduction operation state throughout its entire lifecycle. |
| first_indexed | 2024-04-25T00:08:11Z |
| format | Article |
| id | doaj.art-7fae7d60549f4a40878efedafd9e8170 |
| institution | Directory Open Access Journal |
| issn | 0253-2336 |
| language | zho |
| last_indexed | 2024-04-25T00:08:11Z |
| publishDate | 2024-01-01 |
| publisher | Editorial Department of Coal Science and Technology |
| record_format | Article |
| series | Meitan kexue jishu |
| spelling | doaj.art-7fae7d60549f4a40878efedafd9e81702024-03-14T03:50:43ZzhoEditorial Department of Coal Science and TechnologyMeitan kexue jishu0253-23362024-01-0152117819510.12438/cst.2023-19872023-1987Research on technology of key steps of intelligent ventilation in minesLang ZHANG0Yanqing LIU1CCRI Tongan (Beijing) Intelligent Control Technology Co., Ltd., Beijing 100013, ChinaCCRI Tongan (Beijing) Intelligent Control Technology Co., Ltd., Beijing 100013, ChinaThe process steps of intelligent ventilation in mines were proposed, which could make the ventilation system more orderly and controllable. The process of intelligent ventilation in mines was divided into six process sections according to the production process, namely perception monitoring, analysis and diagnosis, intelligent decision-making, scheme approval, remote centralized control and joint control, and execution feedback, which included a total of 24 specific process steps. The input and output elements of each process step and the functional logical relationship between the process steps were clarified. According to the concept of “overall plan of the mine ventilation system+key refinement of the mining air area”, the scheme for implementing the intelligent ventilation process of the entire mine system and two refined intelligent ventilation process application scenarios for the coal mining and excavation working faces were proposed. The intelligent ventilation process steps of the mine were integrated into specific application scenarios. In order to achieve intelligent ventilation application scenarios, the overall architecture of the mine intelligent ventilation system was optimized based on the logical layering concept. The mine intelligent ventilation control platform consisting of hardware driver layer, functional module layer, computing processing layer, data storage layer, and data acquisition layer was planned and designed. The four key process sections of intelligent ventilation involved ten key process sections,which were ventilation perception monitoring, analysis and diagnosis, intelligent decision-making, remote centralized control and joint control. The ten key process steps included monitoring and perception of air volume and wind speed, online monitoring of ventilation resistance, analysis of air volume and pressure in the entire air network, identification and identification of disaster sources, calculation of dynamic air demand in mines, diagnosis of ventilation system faults, decision-making of on-demand air volume control plans, decision-making of emergency air control plans, unmanned remote air control, and unmanned emergency air control. The current technological status of the ten key process steps were summarized and analyzed, and the technical implementation paths for the ten key process steps were proposed. Through iterative upgrades of various intelligent ventilation key technologies, the mine ventilation system was ultimately achieved to be in the stable, reliable, safe, controllable, efficient, energy-saving, and emergency disaster reduction operation state throughout its entire lifecycle.http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2023-1987intelligent ventilationventilation processcontrol platformintelligent decision-makingdata acquisition |
| spellingShingle | Lang ZHANG Yanqing LIU Research on technology of key steps of intelligent ventilation in mines Meitan kexue jishu intelligent ventilation ventilation process control platform intelligent decision-making data acquisition |
| title | Research on technology of key steps of intelligent ventilation in mines |
| title_full | Research on technology of key steps of intelligent ventilation in mines |
| title_fullStr | Research on technology of key steps of intelligent ventilation in mines |
| title_full_unstemmed | Research on technology of key steps of intelligent ventilation in mines |
| title_short | Research on technology of key steps of intelligent ventilation in mines |
| title_sort | research on technology of key steps of intelligent ventilation in mines |
| topic | intelligent ventilation ventilation process control platform intelligent decision-making data acquisition |
| url | http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2023-1987 |
| work_keys_str_mv | AT langzhang researchontechnologyofkeystepsofintelligentventilationinmines AT yanqingliu researchontechnologyofkeystepsofintelligentventilationinmines |