工业数据融合与互操作关键技术研究OA

Against the backdrop of the accelerated development of industrial intelligence,industrial data has become a key production factor.However,its low quality,heterogeneity,fragmentation,and semantic disconnection have restricted cross-system applications.This paper proposes a technical architecture for industrial data fusion and interoperability,systematically studying three key technologies:data standardization,data quality processing,and data annotation.It constructs a standardized promotion path,introduces a large model-driven dynamic self-closed-loop quality processing system,and establishes a scenario-oriented annotation evaluation model to achieve controllable and quantifiable assessment of the annotation process.The related research provides methods and technical support for the construction of a high-quality industrial data application environment.