Historical Digital Twin Modeling for Object State Subscription
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Solution Overview
Problem
Existing digital twin technologies lack specialized methods for managing the historical state of target objects, leading to inefficiencies in digital management and information accuracy.
Innovation Solution
A method and apparatus for twinning and subscribing to the historical state of a target object by establishing object models with time attributes, association relationships, and generating records to capture and manage historical data accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital twin technology is applied to industrial production elements, then production supervision capability is improved, but the lack of specialized historical state management methods reduces information accuracy
Solution Approach 1:
The patent segments the digital twin system into multiple object models (target object model and sub-object models) with hierarchical association relationships. Each object model independently manages its own historical state data with time attributes, allowing precise tracking of specific components while maintaining overall system supervision capability.
Solution Approach 2:
The patent introduces a time dimension to traditional digital twin technology by adding time attributes to object models. This enables the system to not only represent the current state but also historical states at different time points, transforming the digital twin from a static snapshot to a dynamic temporal record.
2Measurement precision
If object models with time attributes are established for historical state management, then information accuracy is improved, but system complexity increases
Solution Approach 1:
The patent divides the complex historical state management system into multiple independent object models, each responsible for specific target objects or sub-objects. This segmentation allows each model to manage its own time-series data independently, reducing the complexity burden on any single component while maintaining comprehensive historical tracking capability.
Solution Approach 2:
The patent creates simplified digital copies (object models) of physical objects that inherit the same attribute structure but exist in the digital domain. These copied models can store and process historical time-series data without affecting the actual physical objects, reducing system complexity by separating digital representation from physical reality.
3Productivity
If hierarchical association relationships are established between object models, then management efficiency is improved, but the complexity of model relationships increases
Solution Approach 1:
The patent segments the system into hierarchical object models where target object models and sub-object models are clearly distinguished. Each level manages its own data independently, and the hierarchical structure allows efficient querying and management by breaking down complex systems into manageable segments with defined boundaries.
Solution Approach 2:
The patent introduces association relationships as intermediary mechanisms that connect object models at different hierarchical levels. These associations act as mediators that enable efficient data retrieval and relationship management without requiring direct complex interactions between all components, simplifying the overall system architecture.
Data Source
AI summary
Provided in the disclosure are a method and apparatus for twinning and subscribing to a historical state of a target object. The method includes: for a target object and at least one sub-object affiliated with the target object, respectively establishing a target object model and at least one sub-object model, the target object model and the at least one sub-object model each comprise a time attribute; setting the values of the time attributes in the target object model and the at least one sub-object model to be historical times, the historical times are used for indicating times corresponding to data in the target object model and data in the at least one sub-object model; establishing a first association relationship between the target object model and the at least one sub-object model, the first association relationship is used for associating the at least one sub-object model with the target object model.