Electrical treeing is one of the effects of partial discharges in the solid insulation of high-voltage electrical insulating systems. The process involves the formation of conductive channels inside the dielectric. Acoustic emission (AE) is a method of partial discharge detection and measurement, which belongs to the group of non-destructive methods. If electrical treeing is detected, the measurement, recording, and analysis of signals, which accompany the phenomenon, become difficult due to the low signal-to-noise ratio and possible multiple signal reflections from the boundaries of the object. That is why only selected signal parameters are used for the detection and analysis of the phenomenon. A detailed analysis of various acoustic emission signals is a complex and time-consuming process. It has inspired the search for new methods of identifying the symptoms related to partial discharge in the recorded signal. Bearing in mind that a similar signal is searched, denoting a signal with similar characteristics, the use of artificial neural networks seems pertinent. The paper presents an effort to automate the process of insulation material condition identification based on neural classifiers. An attempt was made to develop a neural classifier that enables the detection of the symptoms in the recorded acoustic emission signals, which are evidence of treeing. The performed studies assessed the efficiency with which different artificial neural networks (ANN) are able to detect treeing-related signals and the appropriate selection of such input parameters as statistical indicators or analysis windows. The feedforward network revealed the highest classification efficiency among all analyzed networks. Moreover, the use of primary component analysis helps to reduce the teaching data to one variable at a classification efficiency of up to 1%.

The paper presents results of research of electrical treeing of solid dielectrics with the method of acoustic emission (AE). The study was performed with an alternating voltage of 50 Hz in the range up to 21 kV (RMS) on methyl polymethacrylate or crosslinked polyethylene samples. They were of cuboidal shape of the dimensions 25 × 10 × 4 mm. One of the cuboid sample walls of the dimensions 25×4 mm was covered with a conducting paint. On the opposite wall, a surgical needle of T-25 type was screwed. The distance between the electrodes (the needle and the wall covered with a conducting paint) was in the range 0.5-2.0 mm. Registered signals were denoised with wavelet transformation method and then there were analyzed. The following parameters were analyzed: a sum and rate of acoustic emission counting, a sum and rate of acoustic emission events, RMS value of the electric signal leaving the converter. Spectrum and spectrogram were also analyzed. It was found that AE signals are generated during electrical treeing of solid dielectrics. Values of chosen parameters increased their values when the process begins. There are also some dominant frequencies ranges, different for different kinds of dielectrics, connected with the treeing.

This study aimed to compare concentrations of Zn, Cd, Pb and Cu in wood of Quercus robur and Q. petraea and in the soil on 21 plots in different parts of Polish lowlands. Concentrations of those metals in growth rings taken with an increment borer were measured in 20-year periods. The curves of radial distribution of heavy metals in growth rings are highly variable, but usually a greater variation was observed in sapwood than in heartwood. This attests to transport of metals in the younger, functional xylem, and confirms earlier observations. Quercus petraea accumulated significantly more Zn but less Cd than Q. robur, while concentrations of other metals were similar in both species. No significant correlations between levels of different metals in oak wood were detected, except a strong correlation between Pb and Cd. Concentrations of heavy metals in oak wood were generally not correlated with their concentrations in the soil. Most of the forest stands can be regarded as free from pollution with heavy metals.

The work was aimed at studying of standard potentials of commonly used metallic dental materials and determining of the effect of saliva conductivity and reaction on value of the potentials. The following materials have been examined: gold alloy (a material used for crowns and bridgeworks), chromium-cobalt alloy (for frameworks in removable partial dentures), and silver amalgams (used for fillings) manufactured by three different companies.Taking into account that mucosa makes one of the electrodes existing in oral cavity the rest potentials of mucosa have been in vivo measured in several patients. Their values, converted with respect to NHE, oscillated within the range from þ 0.31 V to þ 0.47 V.Among metallic dental materials examined in the experiment maximal standard potential was found for the gold alloy, further materials having lower potentials, in decreasing order, were chromium-cobalt alloy, and the amalgams Amalcap Plus, ANA 2000 and Septalloy.Significant differences between standard potentials of examined materials and mucosa indicate spontaneous formation of galvanic cells of electromotive force reaching even about 0.6 V.