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

TL;DR

This paper presents a modular semantic model and a method for integrating differential equations into knowledge graphs to better represent time-continuous behavior in Cyber-Physical Systems, validated in aviation maintenance.

Contribution

It introduces reusable ontological artifacts and a method to embed differential equations into knowledge graphs, reducing manual effort and enhancing contextualization.

Findings

Differential equations of a complex Electro-Hydraulic Servoactuator are represented in a knowledge graph.

The artifacts enable contextualization of behavioral models with lifecycle data.

Validation confirms practical applicability in aviation maintenance.

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.