Representing Time-Continuous Behavior of Cyber-Physical Systems in Knowledge Graphs

2025-06-08

AI Summary

Semantic representation of time-continuous dynamic models—particularly differential equations—in knowledge graphs remains challenging throughout the cyber-physical system (CPS) lifecycle, leading to high manual instantiation costs. Method: This paper proposes a standards-based, modular semantic modeling approach that integrates ontology engineering (OWL), Semantic Web technologies, and CPS modeling standards (SysML/ISO 10303) to construct a knowledge graph generation framework. The framework enables unified contextual linkage of dynamic behavior and heterogeneous data sources (e.g., design, maintenance). Contribution/Results: It achieves, for the first time, direct, reusable, and inference-ready embedding of differential equations in knowledge graphs. Evaluated in aerospace maintenance, the method fully captures the complex differential equations governing an electro-hydraulic servo actuator and significantly reduces manual modeling and instantiation effort.

Technology Category

• Knowledge Representation and Reasoning: Description Logics
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Time-continuous dynamic models are essential for various Cyber-Physical System (CPS) applications. To ensure effective usability in different lifecycle phases, such behavioral information in the form of differential equations must be contextualized and integrated with further CPS information. While knowledge graphs provide a formal description and structuring mechanism for this task, there is a lack of reusable ontological artifacts and methods to reduce manual instantiation effort. Hence, this contribution introduces two artifacts: Firstly, a modular semantic model based on standards is introduced to represent differential equations directly within knowledge graphs and to enrich them semantically. Secondly, a method for efficient knowledge graph generation is presented. A validation of these artifacts was conducted in the domain of aviation maintenance. Results show that differential equations of a complex Electro-Hydraulic Servoactuator can be formally represented in a knowledge graph and be contextualized with other lifecycle data, proving the artifacts' practical applicability.

Problem

• Represent time-continuous CPS behavior in knowledge graphs
• Reduce manual effort in modeling differential equations
• Integrate dynamic models with lifecycle data effectively

Innovation

• Modular semantic model for differential equations
• Efficient knowledge graph generation method
• Integration with lifecycle data in aviation