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Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems
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Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems
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Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems
Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems
Journal Article

Hierarchical Decoupling Digital Twin Modeling Method for Topological Systems: A Case Study of Water Purification Systems

2026
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Overview
Digital twins (DTs) have seen widespread application across industries, enabling deep integration of cyber–physical systems. However, previous research has largely focused on domain-specific DTs and lacks a universal, cross-industry modeling framework, resulting in high development costs and low reusability. To address these challenges, this study proposes a DT modeling method based on hierarchical decoupling and topological connections. First, the system is decomposed top–down into three levels—system, subsystem, and component—through hierarchical functional decoupling, reducing system complexity and supporting independent component development. Second, a method for constructing component-level DTs using standardized information sets is introduced, employing the JSON-LD language to uniformly describe and encapsulate component information. Finally, a topological connection mechanism abstracts the relationships between components into an adjacency matrix and assembles components and subsystems bottom–up using graph theory, ultimately forming the system-level DT. The effectiveness of the proposed method was validated using a typical surface water purification system as a case study, where the system was decomposed into four functional subsystems and 12 types of components. Experimental results demonstrate that the method efficiently enables automated integration of DTs from standardized components to subsystems and the complete system. Compared with conventional monolithic modeling approaches, it significantly reduces system complexity, supports efficient component development, and accelerates system integration. For example, when the number of components exceeds 300, the proposed method generates topology connections 44.69% faster than direct information set traversal. Consequently, this approach provides a novel and effective solution to the challenges of low reusability and limited generality in DT models, laying a theoretical foundation and offering technical support for establishing a universal cross-industry DT modeling framework.