ZHU Qing, WANG Suozhi, DING Yulin, ZENG Haowei, ZHANG Liguo, GUO Yongxin, LI Hankan, WANG Wanqi, SONG Shubao, HAO Rui, CHENG Zhibo. A Method of Safety-Quality-Schedule Knowledge Graph for Intelligent Management of Drilling and Blasting Construction of Railway Tunnels[J]. Geomatics and Information Science of Wuhan University, 2022, 47(8): 1155-1164. DOI: 10.13203/j.whugis20210573
Citation: ZHU Qing, WANG Suozhi, DING Yulin, ZENG Haowei, ZHANG Liguo, GUO Yongxin, LI Hankan, WANG Wanqi, SONG Shubao, HAO Rui, CHENG Zhibo. A Method of Safety-Quality-Schedule Knowledge Graph for Intelligent Management of Drilling and Blasting Construction of Railway Tunnels[J]. Geomatics and Information Science of Wuhan University, 2022, 47(8): 1155-1164. DOI: 10.13203/j.whugis20210573

A Method of Safety-Quality-Schedule Knowledge Graph for Intelligent Management of Drilling and Blasting Construction of Railway Tunnels

  •   Objectives  The complex and dangerous mountainous environment, uncertain geographical and geological conditions are the key factors affecting the safety, quality and schedule of railway tunnel construction.
      Methods  Orient to intelligent and precise construction management, this paper proposes a top-down and bottom-up combination of railway tunnel drill safety-quality-schedule knowledge graph construction method, clarifies the conceptual connotation and semantic relationship for the five key elements of man-machine-material-method-environment(4M1E) related to safety-quality-schedule during the construction of railway tunnels, and designs a two-way collaborative construction method of mode layer from top to bottom and data layer from bottom to top, then introduces key technologies such as data acquisition and knowledge extraction.
      Results  Taking the construction event of the Kangding No. 2 railway tunnel exit work area as an example, we construct a case knowledge graph. The results show that the knowledge graph constructed by the method in this paper finely depicts the key element attributes that affect safety-quality-schedule, the semantic relationship between the elements, and the mutual feedback relationship, etc.
      Conclusions  Our proposed method provides key support for the overall systemic intelligent management of safety-quality-schedule in the whole process of railway tunnel drilling and blasting construction, and also lays the foundation for the digital twin of railway tunnel engineering.
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