Précédent|Prochain

Design and key technology research of industrial geographic information system

  • role： First author第一作者
  • Affiliation：

    Insitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

  • Email：sjmao@pku.edu.cn
  • Introduction：毛善君，研究方向为智能矿山专用地理信息系统管理平台研发。E-mail： sjmao@pku.edu.cn
MAO Shanjun1,  
  • Affiliation：

    Beijing Longruan Technology Co., Ltd., Beijing 100190, China

ZHANG Pengpeng2,  
  • Affiliation：

    Insitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

ZHANG Haoyuan1,  
  • Affiliation：

    Beijing Longruan Technology Co., Ltd., Beijing 100190, China

CHEN Jinchuan2,  
  • Affiliation：

    Insitute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China

LI Mei1,  
  • Affiliation：

    Beijing Longruan Technology Co., Ltd., Beijing 100190, China

CHEN Huazhou2

résumé

Since the emergence of Geographic Information System (GIS) theory, technology, and software and hardware systems in the 1960s, it has been widely applied in traditional geosciences, digital cities, intelligent transportation, high-technology warfare, and other fields. On a global scale, the construction of intelligent mines and intelligent plants is the trend, the related workshops, equipment, components, and working environment are also geographical spatial objects, and spatial relationships exist among these entities. Therefore, based on the analysis of the current research and application status of traditional or existing GIS in the industrial field, this paper proposes the concept of Industrial Geographic Information System (IGIS). Based on the theory and methods of Temporal Geographic Information System (TGIS), IGIS comprehensively utilizes the information technologies such as the Internet of things, big data, digital twins, and industrial control, faces the need of intelligent production and manufacturing in the industrial field, through expressions of spatiotemporal modeling and spatial relationship of the entire scene of industrial production, equipment subsystems or components, and the entire production, and constructs a bidirectional mapping and collaborative linkage framework between digital scenes and geographic physical scenes to achieve data collection, transmission, storage, query, analysis, control, inspection, and collaborative work for the safety production of industrial spatial objects, and to provide a visual remote digital twin control platform or system for intelligent plants and intelligent mines.The research objects of IGIS have multidimensional characteristics such as macro and micro, static and dynamic, and visualization and control. Industrial objects are in dynamic changes and interconnected state, requiring feedback on the digital and physical worlds, which is a complex giant system. This paper proposes a composite spatiotemporal object model for IGIS, which is elaborated in an object-oriented manner from three dimensions: (1) In the temporal change dimension, a spatiotemporal version of the spatial object is established, and the entire spatiotemporal change in version increments is recorded. (2) In the dimension of object features, following the geometric and attribute feature expression methods of traditional geographic information system, an extensible integrated expression system for geometry and attributes of macro and micro spatial object is set up. (3) In the behavioral interoperability dimension, the behavioral state characteristics of various industrial spatial objects are demonstrated based on the business process needs of various industrial objects, and the response method of objects to their own attributes and external driving data are examined.Based on the composite spatiotemporal object model, this paper designs key functional modules such as multiscale data management, macro and micro integrated display, spatiotemporal object spatial analysis, and industrial object adaptive response and control, and proposes the IGIS technical framework. Based on unified data standards, the framework from bottom to top includes equipment layer, data acquisition and transmission layer, IGIS platform layer, business service layer, and application decision layer: (1) The equipment layer acts as the data collector and the executor of decision execution information. (2) The data acquisition and transmission layer is a channel for connection and interaction between the equipment layer and the upper layer resources, which is connected to the IGIS platform layer and the business service layer through the industrial network. (3) The IGIS platform layer is the core of the entire system, including various functions and modules to achieve adaptive response and intelligent control of industrial production processes. (4) The business service layer is responsible for the aggregation, storage, sharing, fusion, and intelligent analysis and processing of industrial production scene and process data. (5) The application decision-making layer is composed of intelligent comprehensive control centers established on many subsystems, completing intelligent production scheduling and command.Finally, key technical issues such as data standard specifications, spatiotemporal data collaborative processing, industrial environment digital twins, industrial equipment digital twins, spatiotemporal data intelligent analysis, and configuration control are elaborated, and solutions are provided to achieve integrated topological expression, storage. Analysis and collaborative control provide a unified TGIS remote control platform. The platform has been preliminarily applied in multiple coal mines and coal preparation plants in China, verifying the practicality and feasibility of the system.

mots-clés

remote sensing;Industrial Geographic Information System (IGIS);intelligent mine;intelligent plant;digital twin;visual management and control

References

  1. 1.
    Bhargava P, Jain A, Singh S and Thakur V K. 2015. GIS - SCADA: integration and applications in Distribution network//2015 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC). Melmaruvathur: IEEE: 354-357
  2. 2.
    Chen J, Liu J J and Tian H B. 2022. Basic directions and technological path for building 3D realistic geospatial scene in China. Geomatics and Information Science of Wuhan University, 47(10): 1568-1575
  3. 3.
    Chen S P. 1991. Geo-system and geo-information system. Acta Geographica Sinica, 46(1): 1-7
  4. 4.
    Dang A R and Ding H. 1996. A study on GIS application in coal mining. Remote Sensing of Environment China, 11(3): 220-226
  5. 5.
    Garramone M, Moretti N, Scaioni M, Ellul C, Re Cecconi F and Dejaco M C. 2020. BIM and GIS integration for infrastructure asset management: a bibliometric analysis. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, VI-4/W1-2020: 77-84
  6. 6.
    Gong J Y. 2004. Review of the progress in contemporary GIS. Geomatics and Spatial Information Technology, 27(1): 5-11
  7. 7.
    Gong J Y and Gao W X. 2006. Sharing and interoperability of geospatial information. Geomatics World, 4(3): 18-27
  8. 8.
    Gong J Y and Xia Z G. 1997. An integrated data model in three dimensional GIS. Journal of Wuhan Technical University of Surveying and Mapping, 22(1): 7-15
  9. 9.
    Han M. 2020. Research on the Evolution of Ningde Industrial Historical Pattern based on GIS Technology. Fuzhou: Fuzhou University
  10. 10.
    Huang X B, Wang Z L, Gao X and Qian L J. 2021. Design of power industry geographic information system (GIS) based on virtual reality technology. Information Technology, (7): 31-37
  11. 11.
    Kang Y F. 2018. Design and implementation of geographic information system for urban industrial industry. Mine Surveying, 46(4): 15-18, 36
  12. 12.
    Li L. 2022. Research on the construction of digital twin plant based on design. Automation in Petro-Chemical Industry, 58(4): 73-77
  13. 13.
    Liu B, Wang M S, Li Y, Chen H L and Li J Q. 2021. Deep learning for spatio-temporal sequence forecasting: a survey. Journal of Beijing University of Technology, 47(8): 925-941
  14. 14.
    Liu Y Y, Yun P and Du H Y. 2023. Integrated application of BIM and GIS for aviation industry plant -- the construction of 3D underground pipeline information system. Journal of Information Technology in Civil Engineering and Architecture, 15(1): 55-61
  15. 15.
    Mao S J, Cui J J, Wang S B, Tu X Z, Zhang P P and Li M. 2020. Construction of information sharing platform of mine safe production for intelligent mining. Journal of China Coal Society, 45(6): 1937-1948
  16. 16.
    Mao S J, Yang N S, Gao Y Q, Zhang P P and Wu D Z. 2018. Design and key technology research of coal mine distributed cooperative “one map” system. Journal of China Coal Society, 43(1): 280-286
  17. 17.
    Schabus S and Scholz J. 2015. Geographic Information Science and technology as key approach to unveil the potential of Industry 4.0: how location and time can support smart manufacturing//2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO). Colmar: IEEE: 463-470
  18. 18.
    Shao Q Q, Zhou C H, Shen X Q and Yang C J. 2003. Operational GIS and RS technology and methods for marine fishery. Journal of Remote Sensing (in Chinese), 7(3): 194-200
  19. 19.
    Shi Y R, Wan D F, Li S Y and Lü Z Y. 2009. Research of vehicle routing problem based on GIS. Systems Engineering - Theory and Practice, 29(10): 76-84
  20. 20.
    Song G F, Zhong E S, Wu Z F, Li S J, Cai W W and Wang S H. 2019. Four key technologies of the next generation GIS platform. Journal of Geomatics, 44(1): 1-8
  21. 21.
    Su F Z, Wu W Z, Zhang Y, Kang L and Li X E. 2020. From geographic information system to intelligent geographic system. Journal of Geo-Information Science, 22(1): 2-10
  22. 22.
    Sun D H, Jiang T, Zhou Q Y and Zhang Q Y. 2011. Application of 3D laser scanning technology in industrial 3D GIS. Bulletin of Surveying and Mapping, (8): 90-91
  23. 23.
    Tao F, Liu W R, Liu J H, Liu X J, Liu Q, Qu T, Hu T L, Zhang Z N, Xiang F, Xu W J, Wang J Q, Zhang Y F, Liu Z Y, Li H, Cheng J F, Qi Q L, Zhang M, Zhang H, Sui F Y, He L R, Yi W M and Cheng H. 2018. Digital twin and its potential application exploration. Computer Integrated Manufacturing Systems, 24(1): 1-18
  24. 24.
    Verma P and Verma S. 2012. GIS - SCADA Integration: Approach for Power Distribution. Koln: LAP Lambert Academic Publishing
  25. 25.
    Wang G F, Ren H W, Pang Y H, Cao X G, Zhao G R, Chen H Y, Du Y B, Mao S J, Xu Y J, Ren S H, Cheng J Y, Liu S P, Fan J D, Wu Q Y, Meng X J, Yang J Z, Yu B J, Xuan H B, Sun X K, Zhang D Z and Wang H B. 2020. Research and engineering progress of intelligent coal mine technical system in early stages. Coal Science and Technology, 48(7): 1-27
  26. 26.
    Wu P F, Liu Y S, Tan Y and Li J F. 2019. Advances and trends of integration between GIS and BIM. Geomatics and Spatial Information Technology, 42(1): 1-6
  27. 27.
    Yang J Y, Yang X Z, Liu R, Gao X, Ma Q, Li X Y, Xiao M J, Lu T Q and Liu H. 2020. Integrated data visualization reconstruction technology of power grid combined with GIS. Bulletin of Science and Technology, 36(4): 56-62
  28. 28.
    Zhou J, Li P G, Zhou Y H, Wang B C, Zang J Y and Meng L. 2018. Toward new-generation intelligent manufacturing. Engineering, 4(1): 11-20

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website