A multipole-based effect catalog system for the systematic identification of potential measurands

Abstract

Caused by the progressing digitalization in mechanical engineering, a significant demand for information about characteristic process and state variables of technical systems arises. However, since it is oftentimes neither obvious what nor how to measure, the integration of measuring functions, in particular in terms of a retrofit, represents a current challenge in mechanical engineering. In order to overcome this challenge, an approach for the systematic identification of potential measurands is provided in this contribution. For this purpose, the approach of physical effect catalogs is taken up and used for the systematic identification of potential measurands, starting from a physical variable to be determined. Existing catalog systems have two major limitations with respect to the intended identification of cause–effect relationships: They assume an effect to be realized and a consideration of design parameters of a technical system is not intended. These limitations are overcome by linking the fundamental idea of existing catalog systems with the basics of multipole-based modeling. In this way, a multipole-based effect catalog system is developed. It creates the foundation to systematically include the changes and transformations of a process or state variable to be determined into the identification of potential measurands.

Evaluation of the methodical framework for the management of uncertainty in the context of the integration of sensory functions

“…Using these specific start and end points, the functionally extended effect graph allows to identify relationships in form of (interconnected) physical effects between these points that result in data and model uncertainty. By doing that in an automated manner using the graph, the efficiency of the identification process is significantly improved compared to an identification based on an analog effect catalog, e.g., the one by Vorwerk-Handing et al (2023), as originally proposed in Welzbacher et al (2022). Since many physical effects have prerequisites for their occurrence, the results obtained from the graph must then be reviewed by the user to ensure the occurrence of the included physical effects in the system.…”