The Angle of Arrival (AoA) is an important factor in the localization of a wireless sensor network. This paper deals with AoA measurement using omnidirectional antennas. In our case microstrip monopole antennas are used which have radiation patterns with two sharp minimums. Therefore, an algorithm based on an approach where an AoA is obtained along a direction where the measured received strength signal indicator (RSSI) is minimal. Multiple stationary microstrip antennas are placed on a printed circuit%board and no moving parts are needed for measurement. In comparison with rotating antennas this simple method has lower resolution. We show that the resolution can be improved using interpolations and approximations. When using the proposed algorithm, the experimental results for the outdoor measurements reached a root-mean-square error (RMSE) of less than 10, and an indoor environment of less than 25.
F.17 Transfer of existing technologies, know-how, methods and procedures into practice
COBISS.SI-ID: 18354198In this project, we monitored a canal of hydropower station Zlatoličje and acquired signals using ground penetrating radar in the length of 18 km on both sides of canal. In large-scale data, we performed the detection of changes and develop an information system
F.08 Development and manufacture of a prototype
COBISS.SI-ID: 18364182In this project, we developed a system for automatic detection of dents on car's sheet metal. Methods for computer vision were applied for detecting dents, which were iluminated using source of a structured light.
F.06 Development of a new product
COBISS.SI-ID: 18112790We prepared a material, which will be used by students attending 2nd year of electrical engineering at University of Maribor, Faculty of Electrical Engineering and Computer Science, Maribor, Slovenia
D.10 Educational activities
COBISS.SI-ID: 18406166This doctoral dissertation presents a method for optimizing process parameters in the injection molding process of thermoplastic materials, which is implemented in the developed intelligent system %C-3. The proposed method is based on a combined approach containing three methods of artificial intelligence where all the rules and facts, conquered during massive experimental tests on two injection molding machines, are implemented within the knowledge base as well as in the database, and are also transferable. Proper evaluation of the robustness of this production process is shown using the case of a non-linear mathematical model, where a robust control synthesis of injection screw speed for a designed robust controller according to the Glover-McFarlane method, was taken into account regarding the impact of interferences and additive model variations within the Matlab/Simulink environment. During the following, we carried out extensive experimental studies on three selected thermoplastic materials, where we analyzed the effect of process parameters on transverse and longitudinal shrinkages as well on the warping angles of test specimens, together with the measurements of acoustic emission signals. We proved that this non-destructive method would provide practical usages during the production processes in cases of searching for cracks on engraving tools' inserts and humidity detection in thermoplastic materials. We used Gabor wavelet transformation for a more detailed analysis of the captured AE signals within the time-frequency space. In addition the filling studies of the test specimens were carried out using the Moldflow software package, and were the bases for the subsequent morphological investigations using a scanning electron microscope on the surfaces of the test specimens within the areas of poor orientation regarding the glass fibers.
D.09 Tutoring for postgraduate students
COBISS.SI-ID: 273062144