Measurement Systems Engineering

Contact

Name

Hans-Jürgen Koß

Vice Head of institute / Group Leader Measurement Systems Engineering

Phone

work: +49 241 80 95386

Email

E-Mail: Send Email

"How can we characterize technical processes efficiently and precisely - without influencing them in the course of doing so?"

We deal with this question in the working group Measurement Systems Engineering. We focus on the development of contact-free optical measurement methods and systems. Optical techniques allow the direct investigation of thermodynamic and other technical processes without influencing them, e.g., by inserting measuring probes or taking sample material. The in-situ measurement techniques used can analyze processes with high spatial and/or temporal resolution.

Relevant parameters include state variables such as temperature, pressure, and composition, dynamic process variables such as flow and reaction rate, as well as reagent and product properties (e.g. purity and morphology).

Application

Reliable experimental data are essential both for basic research (e.g. for the construction and validation of process models) and for optimal resource-efficient process control and quality assurance of existing industrial processes.

The fields of application of our measurement techniques, therefore, range from the investigation of basic material properties to the analysis of transport processes in mixtures to the monitoring of reactions in process plants or the use in environmental analysis.

Research approach

For the development of innovative metrological solutions, we pursue a broad approach that includes the entire measurement chain from signal excitation to signal detection and signal evaluation. The optimization and coordination of the individual components with each other adapted to the respective measurement task, enable measurements of the highest quality.

In addition to the use of commercial complete systems, we, therefore, develop measurement systems individually tailored to specific applications. In addition to the hardware, the signal evaluation is decisive for the quality of the measurement information, especially for spectroscopic methods. Depending on the initial data situation, we use tools developed in-house, such as physics-based “Indirect Hard Modeling” (IHM) or data-driven machine learning approaches.

Especially for the determination of material data, we combine our optical measurement techniques with micro-fluidic setups, which allows fast measurement of, e.g., phase equilibria or transport properties with minimal material input. Furthermore, we also perform standard analytics such as GC and HPLC as reference measurement techniques to our optical methods.