Work

Utilizing a graph data structure to model physical effects and dependencies between different physical variables for the systematic identification of sensory effects in design elements

Year: 2022

Type: conference-paper

Abstract: Gaining accurate data from technical systems has become of interest, particularly in the context of condition monitoring and predictive maintenance. Hereby it is important to gather precise and reliable data. To accomplish this task, various sensors with different physical effects are used. Depending on the sensor’s position and measurand, different models are necessary to describe the path from the desired variable of interest to the actual measured one. To support designers, a physical effect catalog was digitalized using a graph data structure, which uses the inherent properties of a graph to represent physical variables, physical effects and their relationships. This graph structure together with its applicability in a sensor selection process will be shown in this paper.

Source: Symposium Design for X (DFX)

DOI: 10.35199/dfx2022.09

Authors: Benjamin Kraus, Stephan Matzke, Eckhard Kirchner

Institution: Technische Universität Darmstadt

Language: English

Topic: Sensor Technology and Measurement Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Deutsche Forschungsgemeinschaft

Award: Erarbeitung von Analyse und Synthesemethoden zur Beherrschung von Unsicherheit beim Entwickeln von mechatronischen Systemen mit sensorintegrierenden Maschinenelementen