The results of a study of induction wireless charging methods for batteries of unmanned aerial vehicles (UAVs) are presented. An experimental simulation of energy transfer using inductive coupling has been carried out. The main factors influencing the efficiency of the system are determined: the distance between the coils, the accuracy of their alignment, and heat losses. It is shown that energy losses with increasing distance reach 45%, and when the coils are shifted by 3 cm, the transmission efficiency decreases by more than 45%. Recommendations have been developed to improve efficiency, including optimizing coil materials, increasing the frequency of energy transmission, automating coil alignment, and introducing active cooling. The results obtained form the basis for further improvement of UAV wireless charging systems.
Keywords: wireless energy transmission, induction methods, resonant induction, unmanned aerial vehicles, optimization of charging systems
In the era of transition to Industry 4.0, industrial equipment requires highly efficient solutions to analyze its performance. Modern monitoring and diagnostic systems should ensure reliable identification of possible problems at an early stage, even in difficult operating conditions, with minimal errors. At the same time, it is important that such equipment is affordable and compact for mass use. In this regard, the study compares the capabilities of piezoaccelerometers and MEMS accelerometers for vibration analysis and fault detection of stepper motors. In the course of the work, the main existing methods of vibration analysis of the equipment condition were analyzed, software was developed that implements variants of mathematical models for processing data from inertial orientation sensors. The design of the stand and the software for the MPU-9250 and AP2037-100-03 sensors are described. The results of the implementation and testing of the MPU-9250 and AP2037-100-03 sensors are presented. The purpose of this study was to compare piezoaccelerometers and MEMS accelerometers to evaluate their effectiveness in vibration diagnostics of stepper motors.
Keywords: vibration monitoring, MEMS sensors, piezoaccelerometers, industry 4.0, predictive analytics, vibration analysis