This study describes the development and utilization of a novel setup for measuring the thermal conductivity of polyurethane composites with various nanoparticle contents. Measurements were conducted using both an experimental setup and a professional instrument, the TPS 2500 S, with results demonstrating high agreement with the precision of the measurements. The setup was further validated using a standard reference material with a thermal conductivity of 0.200 W/m/K. Additionally, the reliability of the setup was confirmed by its stability against ambient temperature variations between 20 and 30 degrees Celsius. This research presents a cost-effective method for measuring the thermal conductivity of polyurethane composites. Data processing involves noise reduction and smoothing techniques to ensure reliable results. The setup offers 5% accuracy and proves to be versatile for both research and educational applications.

Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.

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.

The aim of this study was to perform precision measurements of the frequency-temperature dependences of the loss angle tangent of the liquid-solid composite with the FDS Dirana meter. The composite consisted of heavily moistered oil-impregnated pressboard. The moisturization of the pressboard occurred in a manner as close as possible to the process of wetting the insulation in power transformers to a moisture content of (5.0 ± 0.2) wt. %. This value of moisture content was chosen because exceeding this value can lead to transformer failure. The measuring temperature range was from 293.15 K (20 °C) to 333.15 K (60 °C), with a step of 8 K. The measuring frequency range was 0.0001 Hz to 5000 Hz. It was observed that the shape of the frequency dependence of the loss angle tangent for a moisture content of 5.0 wt. % does not depend on the value of the measuring temperature. An increase in temperature leads to a shift of the waveforms into the higher frequency region. This is associated with a decrease in the relaxation time, and its value depends on the activation energy. It was found that a good fit of the waveforms, simulated by Dirana, to the actual tgδ waveforms obtained at temperatures between 293.15 K (20 °C) and 333.15 K (60 °C) requires the introduction of temperatures, higher than the actual insulation temperatures, into the program. It was found that estimating the moisture content for different temperatures using Dirana soft-ware for insulating an oil-impregnated pressboard produced large discrepancies from the actual content. Better results were obtained after an adjustment requiring manual temperature correction towards higher, compared to measured, temperatures. The moisture content estimated after correction by the Dirana meter ranges from of 4.5 wt. % to 5.7 wt. % and increases almost linearly with increasing measuring temperature. The average moisture content estimated by the Dirana meter for all measuring temperatures is 5.1 wt. % and is close to the actual content (5.0 ± 0.2) wt. %. The uncertainty of the estimate is ±0.43 wt. % and is more than twice as high as the true value.