Bachelor theses / Master theses / Diploma theses / Compulsory internship
Contributions to motion tracking of autonomous flow-following sensor particles in industrial process environments (Id 279)
No current offer!
Data acquisition in large industrial vessels such as biogas fermenters or wastewater treatment plants is limited to local measurement points due to limited access to the vessel and the non-transparency of the fluid. To optimize these kinds of plants, the three-dimensional flow field and the spatial distribution of properties such as temperature and electrical conductivity inside the vessel need to be known. This can be achieved by the autonomous flow-following sensor particles developed by HZDR. Equipped with a pressure sensor, an accelerometer, two gyroscopes and a magnetometer, the sensor particle can track the movement inside the vessels and to infer the flow field from that. The analysis of the data is done after a successful recovery from the vessel. Therefore, algorithms of any complexity can be used to track the motion of the sensor particle.
For the extension and especially for the improvement of the motion tracking we offer the following tasks, from which we can agree on a topic for a thesis or an internship:
- Development of motion tracking algorithms
- Characterization and error correction of the sensors
- Intelligent sampling for the sensors
- Experimental investigation of the maximal acceleration on a stirrer
- Development of firmware to cover several data acquisition scenarios
- Development of an end-user program for the configuration and data analysis of the gathered data
Department: Experimental Thermal Fluid Dynamics
Contact: Buntkiel, Lukas, Dr. Reinecke, Sebastian
Requirements
Studies in the area of electrical, mechatronic, mechanical engineering or similar
- Basics of measurement uncertainty, digital signal processing
- Data analysis in Python
- Independent and structured way of working
Conditions
- Start possible at any time
- Duration according to the respective study regulations
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