This paper deals with the problem of traffic noise in urban areas in terms of noise mapping. It explains in detail the Mobile Crowdsensing (MCS) method and, furthermore, compares the results obtained with this method with the results gained from the standard method that uses a sound level metre. The research done in this paper shows that the MCS method can make noise mapping easier, cheaper and less time-consuming in terms of creating representative noise maps developed on measurements but also noise maps developed on calculations and simulations. The main idea is to show that accuracy and precision of measurements obtained by using calibrated smartphones are acceptable. The paper suggests that when using the smartphone measurement application, the calibration of the measurement chain can be done in free field with class 1 sound level metre, and noise map can be checked in a much larger number of points (in comparison with the standard measurement method) and therefore, smartphones can be used as instruments for creating or even checking final noise maps in urban environment. Another advantage of this method is that citizens can engage in noise monitoring in urban areas and become aware of the noise pollution in their cities.

Possibilities to use unmanned aerial vehicles (UAVs) are rapidly growing. With the development of battery technologies, communication, navigation, surveillance, and autonomous systems in general, many UAVs are expected to operate at relatively low altitudes. Thus, the problem of UAV noise impact on human health and well-being will be more pronounced. In this paper, we conducted noise measurements of two UAVs of different performance (quadrotor and hexarotor) in flying up and down, hovering, and overflight procedures. Respondents of good hearing who were confirmed by audiogram measurement and had participated in the survey during UAV noise measurement gave their subjective assessments on the UAV noise perception. UAV noise measurements and subjective respondents’ assessments were analysed and related. UAV noise analysis showed that the parameters measured at the same measurement point for the hexarotor were higher than those for the quadrotor in flying up and down and flying-over procedures. Low frequency noise was present in the noise spectrum of both drones. Participants were able to distinguish between the noise of UAVs and had a generally more negative experience with the hexarotor. Regardless of the noise perception, more than 80% of the respondents believe there are more pros than cons for UAV introduction into everyday life.

This paper presents a detailed analysis of quadcopter noise emitted in different flight regimes and suggests an innovative approach to quadcopter sound detection. Currently, quadcopters have become extremely popular and are used for various applications. In some case scenarios, these applications are not legal; therefore, they represent a threat, and early detection of quadcopters becomes imperative. However, conventional detection with radars and infrared cameras does not provide satisfactory results, since some quadcopters have relatively small dimensions, and their motors have low heat emissions. Thus, this paper focuses on the noise emitted by quadcopters, which is connected to the changing revolutions per minute of the electric quadcopter motors. Thus, the paper connects the unique quadcopter features with the emitted sounds, which can be used for detection in different acoustic environments. The suggested algorithm uses signal processing with a nonlinear function, which results in new spectral lines that correspond to rotational speed differences between the front and rear motors. The analysis shows that the processed signal mixed with a traffic noise signal can be detected when the level reaches 3 dB lower than the level of the surrounding noise.

The theme of this work is characterization of an ultrasonic low-frequency device, driven at an excitation frequency of around 25 kHz at different electrical excitation levels by using three different methods as proposed in IEC 61847 and IEC 61088 standards. The first method is based on the electromechanical characterization of the device. It consists of measuring the input electrical impedance around the excitation frequency in the unloaded and loaded conditions at a low level excitation voltage of 1 V. The equivalent RLC electrical circuit parameters of an unloaded and loaded device are determined in an anechoic tank and in a vessel at different immersion depths and tip positions in a complex geometry. The electroacoustic efficiency factor of the method is determined by knowing the real part of the radiation resistance and mechanical loss resistance which are transformed into an equivalent RLC electrical circuit of the transducer. The second method consists of measuring the spatial pressure distribution of an ultrasonic device near pressure release boundary in an anechoic tank. The acoustic reciprocity principle is used to determine the derived acoustic power of an equivalent point source in the form of radially oscillating sphere at the excitation frequency. The third method is based on the measurement of power dissipated in a restricted volume of water by using a calorimetric method. Some of the suggested methods are complicated to apply in the high energy ultrasonic devices whose size is much lower than the wavelength in the loading medium due to the occurrence of strong cavitation activity and influence of the sonotrode tip position in the complex standing wave field. However, the measured acoustic power found by using the three suggested methods is compared by means of the electroacoustic efficiency factor defined for each considered method. In the electromechanical characterization, which is made at low electrical excitation levels (applied electrical power of 1 mW at the series resonance frequency), the calculated maximum electroacoustic efficiency factor is around 48% when the influence of standing waves pattern on the radiation resistance is small. It is approximately the same as the one obtained by measuring the derived acoustic power in an anechoic tank (43%) without cavitation activity in front of the tip. When a strong cavitation activity is present in the loading medium, the bubble cloud has a significant influence on the derived acoustic power which is then dispersed in a broad frequency range and the electroacoustic efficiency factor of the method decreases down to 2%. A significant growth of the input electrical impedance magnitude at the excitation frequency is observed when the cavitation activity is present in front of the tip and when it is compared with the impedance magnitude measured at lower excitation levels without cavitation. The power dissipated in the loading medium almost linearly depends on the applied electrical power, with saturation at higher excitation levels. In the linear operating mode the electroacoustic efficiency factor of the calorimetric method (48%) is comparable with the efficiency factors of two other methods. In the nonlinear operating mode, it is larger (71%) due to a significant amount of heat energy released during the cavitation process.

In this work, the vibrations on the surfaces of the tank wall, stiffeners, and the cover of a 5 MVA transformer experimental model were measured during open-circuit and short-circuit transformer tests. Vibration measurements of a transformer tank side were conducted at discrete points using two different voltage sources in no-load test. Using interpolation functions, the RMS values of acceleration and vibration velocity are visualized and compared for each considered measurement configuration (no-load and load tests and two different excitation sources). Significant differences in mode shapes and amplitudes of vibrations at different frequencies are observed. The maximum RMS values of acceleration, velocity and displacement in the open-circuit test are 0.36 m/s², 0.31 mm/s, and 0.42 µm, respectively. The maximum values in short-circuit test are 0.74 m/s², 1.14 mm/s, and 1.8 µm, respectively. In the short-circuit test, the frequency component of 100 Hz is dominant. In the open-circuit test, the first few 100 Hz harmonics are significant (100 Hz, 200 Hz, and 300 Hz). In addition to the visualization of RMS values during the open-circuit and short-circuit tests, animations of the vibrations are created. Fourier analysis and phase comparison between frequency components are also used to show vibration animations at dominant frequencies in the spectrum (100 Hz harmonics). The visualization of the vibrations at the tank wall surfaces is transferred into 3D space in such a way that all 15 surfaces are mapped to the spatial coordinates of the surfaces so that a 3D model of the acceleration, vibration velocity, and displacement of the transformer tank is shown.