Industrial digital twin is the key support for the transformation of industry to intelligence. The realization of digital twin relies on the integration of whole-process data, which can provide real-time and intelligent decision-making optimization for production management. This paper proposes a digital twin data fusion method based on semantic data dictionary. Firstly, a modeling method of domain data dictionary is designed, and a semantic method is introduced to realize the construction of semantic data dictionary. Then, based on the semantic data dictionary, a semantic similarity calculation method based on multivariate distance weighting is proposed. Finally, the algorithm is tested and verified. The experimental results show that the method in this paper has a significant effect on automatic data fusion in the construction of industrial digital twins.
The development of the Industrial Internet has caused a change that traditional internet technologies gradually sink into the field of industrial manufacturing. Due to the high degree of business coupling at the edge of industrial production, the relationships between the data are complex and difficult to comprehensively analyze and apply. This paper proposes a data semantic association retrieval method for industrial data at the industrial edge. Firstly, the framework of semantic association retrieval of industrial data is established, and then the construction method of inverted table in association retrieval is explained, including the formation method of keyword set and concept set, and the algorithm for realizing semantic association retrieval is given. The algorithm is verified in the actual scene of the test production line, and the results show that the algorithm in this paper is feasible and effective in relational retrieval.
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