Research on Version Difference Detection Method of Metrology Base Platform Based on Knowledge Graph
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Abstract
The metrology base platform serves as the core infrastructure for data management, business operation and standard implementation in the metrology field. Iterative updates of the platform generate multiple versions, and differences in functions, data and rules between versions directly affect the accuracy and stability of metrology work. Traditional version detection methods mainly rely on manual comparison and text retrieval, which suffer from low efficiency, high omission rate and inability to sort out correlation relationships. Taking knowledge graph technology as the core, this paper proposes a version difference detection method for metrology base platforms. This study first analyzes the iteration characteristics of metrology base platform versions and the drawbacks of traditional detection methods, then designs the construction process of a domain-specific knowledge graph for metrology. Combined with the comparison logic of graph nodes, relationships and attributes, a version difference detection model is established, and an experimental scheme is designed to verify the proposed method. The experimental results show that this method can automatically identify differences in data structures, business rules and functional modules across different versions of the metrology base platform, with detection efficiency and accuracy significantly outperforming traditional manual detection and general text comparison methods. This research provides technical references for version management, system operation and maintenance, and standard compliance verification of metrology platforms.
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