Master theses / Diploma theses / Student Assistant

Autonomous flow following sensor particles are used for acquisition of spatially distributed process parameters in industrial processes, such as biogas digesters, waste water treatment basins or bioreactors. The task is focussed on the development of algorithms for reconstruction of the 3D movement trajectory of sensor particles based on data from the onboard inertial sensors, namely acceleration, angular rate and magnetic field, and an additional sensor for vertical position as function of the hydrostatic pressure. A favored approach is based on inertial navigation techniques that apply Bayes filters, e.g. Kalman filters, to fuse the sensor data. The developed algorithms are to be validated experimentally.

• study programs in the fields of electrical engineering, mechatronics, mechanical engineering and related degree programs
• fundamentals of digital signal analysis, Bayes' filters, Kalman-filters, rigid body motion
• experimental skills
• data analysis in Matlab, Octave or C/C++
• self-regulating, independent work methods