Unmanned aerial vehicles (UAVs) are used nowadays in a wide range of applications, including monitoring, mapping, or surveying tasks, involving magnetic field mapping, mainly for geological and geophysical purposes. However, thanks to the integration of ultrasound-aided navigation used for indoor UAV flight planning and development in sensorics, the acquired magnetic field images can be further used, for example, to enhance indoor UAV navigation based on the physical quantities of the image or for the identification of risk areas in manufacturing or industrial halls, where workers can be exposed to high values of electromagnetic fields. The knowledge of the spatial distribution of magnetic fields can also provide valuable information from the perspective of the technical cleanliness. This paper presents results achieved with the original fluxgate magnetometer developed and specially modified for integration on the UAV. Since the magnetometer had a wider frequency range of measurement, up to 250 Hz, the DC (Direct Current) magnetic field and low frequency industrial components could be evaluated. From the obtained data, 3D magnetic field images using spline interpolation algorithms written in the Python programming language were created. The visualization of the measured magnetic field in the 3D plots offer an innovative view of the spatial distribution of the magnetic field in the area of interest.

This article deals with the design and creation of a tensometric measuring system to measure the parameters of an unmanned aerial vehicle (UAV) of the quadcopter type. The system was designed to measure the total UAV thrust and the thrust of its individual motors. The distribution of forces from the UAV motors and their transmission to the sensors was ensured by a specially designed construction, for which the mechanical stresses were simulated and analysed for different modes of the UAV flight. The thrust measurement was performed by four pairs of strain gauges. A measurement system designed in this way and the measured parameters of the UAV can be used for tuning the flight control algorithms applied in the autopilot.

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