基于集合卡尔曼滤波的数字孪生参数场实时更新方法
By using a real-time update method for digital twin parameter fields under the framework of ensemble Kalman filtering, the problem of tracking dynamic changes in formation parameters during engineering construction was solved, achieving real-time updates of the parameter field and reliability of risk assessment, thus preventing safety accidents.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing digital twin technology cannot track the dynamic changes of geological parameters in real time during engineering construction, leading to safety accidents such as excessive surface subsidence, structural deformation, and even collapse. Furthermore, the parameter field update suffers from spatial discontinuities and cross-parameter mechanical imbalances.
A real-time update method for digital twin parameter fields based on ensemble Kalman filtering is adopted. An initial three-dimensional twin scene is established through implicit surface interpolation and triangulation reconstruction driven by spatial discrete sampling data. The sensor layout is optimized by combining finite element multi-condition simulation. Robust assimilation and Bayesian inversion are performed using the ensemble Kalman filtering framework. Spatial compatibility weight constraints and mechanical coupling operator corrections are introduced to achieve continuous and mechanically coordinated updates of the parameter field.
It enables real-time dynamic updating of formation parameters, suppresses spike anomalies driven by local noise, improves the spatial continuity and mechanical consistency of the parameter field, and enhances the reliability of construction risk assessment and the accuracy of decision-making.
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Figure CN122413871A_ABST