Every day, researchers from the Department of High Voltage Engineering at the Faculty of Electrical Engineering and Computer Science carry out numerous experiments to evaluate the properties of electrically insulating materials and components. What has often delighted interested visitors to cultural events in the hall, namely the lively effects of dynamic experiments at high voltage, can lead to problems, particularly when direct current is conducted through the insulators. Interesting electric arcs occur, but are harmful to the material in this context.

How can this "big data" be evaluated? Daniel Fiß from the Institute of Process Engineering, Process Automation and Metrology wants to develop a closed mathematical method based on fuzzy set theory to evaluate test data while taking uncertainties into account. The future tool will then provide information on the reliability of the data.

A promising collaboration that will also enable the two employees Stefan Kühnel (EI) and Daniel Fiß (IPM) to gain further qualifications. The employees and the participating professors Stefan Kornhuber (EI) and Alexander Kratzsch (IPM) met for a kick-off meeting. The project was summarized under the name: "Contribution to the further development and use of big data analysis methods for transient measurement data in process engineering".

The joint project is supported by the Zittau/Görlitz University of Applied Sciences with funds to improve the basic research equipment.