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The paper deals with a special case of identifying the operation mode of an unmanned aircraft (UAV) engine by an acoustic signal (provided that a known type of propellers is used), the main frequency extraction from the signal, and a numerical experiment. A full-scale experiment was performed with the recording of the acoustic signal of a real quadrocopter. The signal is analyzed by the method of frequency filters and Fourier transform. A numerical experiment was performed on a scanned model of a UAV propeller, rotating at a frequency obtained from an acoustic signal. The experiment involved a hybrid finite-volume method on the mesh of the finite element method of the ANSYS CFX simulation environment. The correspondence of the required lifting force with the permissible error is revealed, and as a result, the ability to identify the engine operating mode by an acoustic signal is shown. The field measurements of the acoustic signal are compared with the values recovered from a numerical experiment. A significant amount of data has been obtained suitable for use in the inverse problem and semi-analytic methods.

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Partial discharges result in cable line faults that can occur in defective insulation systems made of rubber, polyethylene, XLPE, and flexible PVC. Insulation defects may occur due to disruptions in their production process, cable installation, and operational conditions. Therefore, the diagnostic and monitoring of partial discharge occurrence in cable insulation help prevent emergencies in damaged cable line sections. Partial discharge registration is a non-destructive diagnostic method that helps assess the cable line condition and localize the detected defects. There are various methods of operational monitoring and partial discharge cause analysis based on operative partial discharge sensors. The assessment of cable line condition depends on the efficiency of signal detection and processing by the sensors used. This article reviews the problems of detecting and localizing partial discharges in cable lines and junction boxes using HFCT and UHF sensors. Having analyzed the capabilities of these sensors, we believe that the combined usage of HFCT and UHF sensors is the best method of detecting and localizing partial discharge within the entire cable system (lines and junction boxes).