Fusion method and engine system based on twin data driving

Abstract

The invention provides a fusion method and engine system based on twin data driving, and the method comprises the following steps: obtaining twin data which comprises holographic three-dimensional data, Internet of Things data, event data and positioning data; constructing a unified space entity identity code of the twin data, and querying and updating the twin data based on the unified space entity identity code; analyzing the twin data to obtain structured data, unstructured data and real-time data; and performing distributed calculation and storage on the twin data based on a data storage and calculation platform. According to the fusion method based on twin data driving and the engine system, a spatio-temporal data three-dimensional model of the real world can be accurately copied, and spatio-temporal variation and tracing capability can be provided.

Description

technical field [0001] The present invention relates to the technical field of digital twins, in particular to a fusion method and an engine system driven by twin data. Background technique [0002] Digital twin is a simulation process that makes full use of physical models, sensor updates, operation history, etc., integrates multi-disciplinary, multi-physical quantities, multi-scale, and multi-probability simulation processes, and completes the mapping in the virtual space to reflect the entire life cycle of the corresponding physical equipment. process. A digital twin is a concept beyond reality that can be viewed as a digital twin of one or more important, interdependent equipment systems. Digital twin is a generally applicable theoretical and technical system that can be applied in many fields, especially in product design, product manufacturing, medical analysis, engineering construction and other fields. [0003] With the advent of the digital twin era, the infrastru...

AI Technical Summary

Problems solved by technology

However, at present, multi-source acquisition equipment is mainly used to collect digital twin data. Due to the different data storage characteristics of each data engine, the technology overlaps and is difficult, most of them are independently stored in different databases and managed separately, resulting in data storage. Layer management is difficult, maintenance is inconvenient, and interaction is difficult, so building a unified multi-source twin big data engine and realizing digital twins will be an inevitable trend

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