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

DS 119: Proceedings of the 33rd Symposium Design for X (DFX2022)

Year: 2022
Editor: Dieter Krause, Kristin Paetzold, Sandro Wartzack
Author: Benjamin Kraus, Stephan Matzke, Peter Welzbacher, Eckhard Kirchner
Series: DfX
Institution: Institute for Product Development and Machine Elements - pmd, Technical University of Darmstadt
Page(s): 10
DOI number: 10.35199/dfx2022.09


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.

Keywords: Sensory function, synthesis method, effect catalog, support tool, SuDE


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