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Volume 52 Issue 10
Oct.  2022
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Article Navigation >  INDUSTRIAL CONSTRUCTION  > 2022  >  52(10): 204-210,235
LIU Zhansheng, SHI Guoliang, WANG Jingchao. RESEARCH ON INTELLIGENT PREDICTION METHOD OF PRESTRESSED CABLE FORCE BASED ON DIGITAL TWINS[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(5): 1-9,123. doi: 10.13204/j.gyjzG20110502
Citation: YANG Hao, YU Fangqiang, GAO Shang, XU Jinglin. Research on Data Fusion of Building Operation and Maintenance Systems Based on Digital Twins and Its Application[J]. INDUSTRIAL CONSTRUCTION, 2022, 52(10): 204-210,235. doi: 10.13204/j.gyjzG22073107
shu

Research on Data Fusion of Building Operation and Maintenance Systems Based on Digital Twins and Its Application

doi: 10.13204/j.gyjzG22073107

  • Shanghai Construction No. 4 (Group) Co., Ltd., Shanghai 200233, China

  • Received Date: 2022-07-31
    Available Online: 2023-03-22
    Abstract
  • The process of mapping data from a building operation and maintenance system to building digital twins is exposed to various problems, such as discrete data, multi-source heterogeneous data, and poorly effective queries, and so on. To solve those problems, a new approach to fusion of building operation and maintenance data was designed and a data fusion system based on digital twins in the aspects of the preparation, access, transformation, integration, and visualization, and etc of building operation and maintenance data. The custom Source Function operator of Flink, data transformation and mapping configurations, and the self-developed stream processing engine and online analytical processing (OLAP) engine were employed to solve the above three issues of building operation and maintenance systems. Finally, a grade-A tertiary hospital in Qingdao was discussed as an example of practical application. The results supported the following conclusions:The proposed data fusion approach could fully meet the various data fusion requirements of the building operation and maintenance system; the proposed data fusion system was capable of successfully accessing, transforming, storing, and visualizing the hospital's over three billion pieces of data from various fields; the proposed data fusion approach also laid a foundation for research and application of digital twin technology.
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