Electric car does not supply all the electric energy, obtained from the electric network, to the wheels in the form of mechanical energy. During such a transformation, a part of this energy is lost. The article endeavours to determine the ener...

In this study, the conductivity and permittivity of electrical pressboard—insulating liquid—water composites were investigated, and the electrical properties of the composites and water were analysed comparatively. Mineral oil and synthetic ester were used as insulating liquids. It was found that the presence of water caused an increase in the permeability of the composite in the frequency range below 100 Hz. The value of static permittivity determined by water in the content of 5 wt. % was approximately 15. To obtain this value caused by liquid water, its volume should be approximately five (oil) and four times (ester) higher than its actual content, respectively. The determined values of the activation energy of the DC conductivity of the composites were several times higher than the values of the activation energy of the conductivity of the liquid water. The experimental values of the dielectric relaxation times were many orders of magnitude higher than the dielectric relaxation times of water. This means that the experimental results obtained for the dielectric permittivity, the activation energy of conductivity and the dielectric relaxation times for moisture electrical pressboard impregnated by mineral oil or synthetic ester exclude the possibility of the presence of liquid water in the composites. It was found that the conductivity of the composites increased exponentially with increasing water content. Such dependencies are characteristic of hopping conductivity, caused by the quantum phenomenon of electron tunnelling between nanometre-sized potential wells. As the increase in conductivity is determined by the presence of water in the composites, therefore, the nanometre potential wells were single-water molecules or nanodrops.

The article describes the non-contact and contact analysis of 1-MVA dry power transformers with epoxy-resin insulation using an acoustic camera and frequency analyzer with automatic sweeping for low-middle frequency areas. Power transformers are most commonly used for construction component (core, windings, taps) analysis. The electrical, non-rotating machine generates electromagnetic and acoustic emissions that can be used to analyze dry transformers during their operation. Non-contact online diagnostic methods have many advantages over offline methods because it is not necessary to shut down the transformer, and also, the condition and behaviour of the machine are analyzed during its normal operation. The article presents the analysis and comparison of structural parts of the distribution dry transformers of the same type and power. The problem of insufficient or incorrect clamp-screw connection was identified using the SFRA (Sweep Frequency Response Analysis) method.

This paper presents a novel diagnostic method that employs the fuel injection system as a sensor for monitoring internal combustion engine pressure, analysing series resistance to detect connector degradation, and evaluating needle movement within the injector’s magnetic core. Experimental results showed that reducing the injector needle opening from 100% to 20% of its maximum displacement caused up to a 35% reduction in peak current amplitude and a 0.2 ms delay in coil charging. Increasing fuel pressure from 0.3 bar to 2.5 bar resulted in a rise in peak current by approximately 35% and an extension of coil charging delay by 0.4 ms. Furthermore, increasing the series resistance from 0.2 Ω to 2.0 Ω reduced the current amplitude by nearly 50% and significantly distorted the waveform, simulating connector oxidation or wear. Comparative analysis of reference and fault current waveforms confirmed that variations in electrical parameters correlate with injector needle displacement, fuel pressure, and resistance changes. Finally, an automated diagnostic system was developed that achieved over 90% accuracy in independently detecting injector faults based on current waveform characteristics.