Comparison of artificial intelligence techniques to failure prediction in contaminated insulators based on leakage current

Contamination in insulators results in an increase in surface conductivity. With higher surface conductivity, insulators are more vulnerable to discharges that can damage them, thus reducing the reliability of the electrical system. One of the indications that the insulator is losing its insulating properties is its increase in leakage current. By varying the leakage current over time, it is possible to determine whether the insulator will develop an irreversible failure. In this way, by predicting the increase in leakage current, it is possible to carry out maintenance to avoid system failures. For forecasting time series, there are many models that have been studied and the definition of which model is suitable for evaluation depends on the characteristics of the data associated with the analysis. Thus, this work aims to identify the most suitable model to predict the increase in leakage current in relation to the time the insulator is outdoors, exposed to environmental variations using the same database to compare the methods. In this paper, the models based on linear regression, support vector regression (SVR), multilayer Perceptron (MLP), deep neural network (DNN), and recurrent neural network (RNN) will be analyzed comparatively. The best accuracy results for prediction were found using the RNN models, resulting in an accuracy of up to 97.25%.

Structure and characteristics of a thin-layer "aluminum - carbon nanotubes" sandwich structure

The study describes a way to produce thin-layer sandwich structures containing layers of aluminum foil and an interlayer filler of carbon nanotubes (CNTs). To obtain a homogeneous structure of the composite, induction heat treatment was used combined with a device providing primary compression of the assembly. To determine the functional characteristics of sandwich structures, the homogeneity of their microstructure and surface conductivity were studied. It was found that the use of CNTs allowed increasing the surface conductivity by a factor of 8.3–9.5 compared to the sandwich structure without filler.

Electrophoresis of tightly fitting spheres along a circular cylinder of finite length

Electrophoresis of a tightly fitting sphere of radius $a$ along the centreline of a liquid-filled circular cylinder of radius $R$ is studied for a gap width $h_0=R-a\ll a$ . We assume a Debye length $\kappa ^{-1}\ll h_0$ , so that surface conductivity is negligible for zeta potentials typically seen in experiments, and the Smoluchowski slip velocity is imposed as a boundary condition at the solid surfaces. The pressure difference between the front and rear of the sphere is determined. If the cylinder has finite length $L$ , this pressure difference causes an additional volumetric flow of liquid along the cylinder, increasing the electrophoretic velocity of the sphere, and an analytic prediction for this increase is found when $L\gg R$ . If $N$ identical, well-spaced spheres are present, the electrophoretic velocity of the spheres increases with $N$ , in agreement with the experiments of Misiunas & Keyser (Phys. Rev. Lett., vol. 122, 2019, 214501).

Surface Phonon Polariton Modes in Suspended Monolayer Hexagonal Boron Nitrides

Dispersion properties and characteristics of transverse magnetic (TM) and transverse electric (TE) surface phonon polaritons (SPhP) in suspended monolayer hexagonal boron nitrides (hBN) was studied extensively. The analytical results show that the hBN based TM (TE) phonon polaritons exist in restsrahlen bands when imaginary surface conductivity is positive. The effective mode index of TM phonon polaritons is much higher than that of TE phonon polaritons with respective values of ~3000 and ~1.0002 which makes TM SPhP more promising in the practical realization. In addition, the propagation length of TE SPhP is less lossy and surpass that of TM SPhP by factor of 104. This study compares these important properties and sheds more insight into their applications in optical communications, photonics and optoelectronics devices.