Digital Twin Virtual Entity Data Association Mapping Based on Binary Space-Time Coding

The association mapping between digital twin virtual entities and real data needs to rely on precise, accurate and consistent data. How to cluster and perceive these data quality problems is an important difficulty in association mapping. Therefore, an associative mapping method of digital twin virtual entity data based on binary space-time coding is proposed. Combined with the modeling language AutomationML, the perception and transmission of digital twin virtual entity data are realized. Based on the digital twin technology and the digital twin of products, processes and resources, the simulation model of the production process of data is established, and the preliminary coding steps of digital twin virtual entities are designed. The experimental results show that the data association mapping of digital twin virtual entities proposed in this paper is reliable and time-consuming.