Industrial data fusion method based on semantic data dictionary for digital twin

Abstract

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.