Daria Wotzka

Indicator analysis of partial discharges measured using various methods in paper-oil insulation

Results of a comparative analysis of two non-dimensional coefficients, calculated based on signals emitted by partial discharges (PD) are presented in the paper. The PD were generated using setups for modeling of three basic types of PD sources, which can occur in paper-oil insulation in power transformers. The following measuring methods were considered: electrical, ultra-high frequency, acoustic emission, and optical spectrophotometry. All measurements, for each of the PD-source configuration using the various methods, were conducted simultaneously in a laboratory under same measurement conditions. Based on the gathered results it was stated that it is possible to recognize the partial discharges form based on the non-dimensional coefficients, which differ in value for all of the considered methods except for the acoustic emission. The main contribution of the research performed lies in the simplicity of the applied signal processing procedure, which can be adopted to a device or system for diagnosis of partial discharges occurring in paper-oil insulation.

Partial discharge simulation in an acoustic model of a power transformer

Methodology and results of a numerical simulation of a partial discharge in an acoustic model of a typical 1 MVA power transformer are presented in the paper. The partial discharge is simulated inside the transformer core as flow of energy that induces acoustic wave. Propagation of the wave is analyzed in the paper.

Application of Optical Spectrophotometry for Analysis of Radiation Spectrum Emitted by Electric Arc in the Air

This paper presents the results of measurement and analysis of optical radiation emitted by a free burning electric arc. The aim was to determine the application possibilities of optical spectrophotometry for detection of electric arcs. The research works considered electric arc generated with a constant voltage supply between two copper electrodes in the air, carried out under laboratory conditions. A high resolution optical spectrophotometer was used for registration of optical radiation. The analyses involved determination of two dimensionless descriptors obtained for the gathered spectra. Moreover, for each of the registered intensity distributions, the energy values were calculated for three frequency ranges. Based on the measured signals, the possibility of application of spectrophotometry for the optical radiation analysis was confirmed. The analysis indicated that the most energy of optical radiation is detected for the range of 200–780 nm, while above 780 nm almost no optical energy is emitted. Spectrophotometric studies performed in the UV-NIR range are of interest since one can obtain information about the structural defects (at lower wavebands) or impurities and/or point defects (at low energies bands). It was also stated that the obtained descriptors may be applied for diagnosis and identification of electric arc purposes.

Modeling A Session-Based Bots' Arrival Process At A Web Server.

The paper deals with the problem of modeling key features of the Web traffic generated by Internet bots, observed at the input of a Web server. Based on real log data of an online store, a set of bot sessions was prepared and analyzed. Three session features connected with bots’ arrival process at the server were analyzed: session interarrival time, request interarrival time, and the number of requests in session. Distributional models for these bot session features were developed using regression analysis and validated through graphical comparisons of histograms for the empirical data and simulated values. As a result, interarrival times of bot sessions and interarrival times of requests in bot sessions were modeled by a Weibull and a Pareto distribution, respectively, and the numbers of requests in session were modeled by a function being a combination of a sigmoid and exponential distributions. The aim of our analysis was to develop a model of a session-based bot arrival process on a Web server which may be then implemented in a bot traffic generator integrated with a Web server simulator.

Modeling a non-stationary bots’ arrival process at an e-commerce Web site

Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real log data for an online store, sessions generated by bots were reconstructed and their key features were analyzed, including the interarrival time of bot sessions, the number of HTTP requests per session, and the interarrival time of requests in session. To deal with the problem of non-stationarity of the Web traffic, chunks associated with times of day were distinguished based on the intensity of bot sessions’ arrivals and then features of sessions in individual time chunks were analyzed separately. Using regression analysis, a mathematical model of the bots’ traffic features was developed and implemented in a bot traffic generator. Our findings confirm the existence of a heavy-tail in bot traffic features’ distributions. The bots’ session interarrival times and request interarrival times are best modeled by a Weibull and a sigmoid distributions, respectively, while the model proposed for the numbers of requests per bot session is based on a hybrid function being a combination of one exponential and two normal distribution functions. The suitable fit of the model was confirmed by the high correlation of the real and model data. Furthermore, a visual inspection of the simulation results showed that the estimated values represent distributions close to those of the empirical data.

Application of Non-destructive Testing for Measurement of Partial Discharges in Oil Insulation Systems

The subject area regards to metrology and measurement methods applied for nondestructive investigation of electrical discharges occurring in oil insulation systems of high-voltage devices. The main aim of performed research studies is a detailed and multivariate analysis of physical phenomena associated with generation of electrical partial discharges (PD), which occur in oil insulation of electrical equipment. An important cognitive component was the verification whether the form of PD has an effect on the energy contribution of the physical phenomena associated with their generation. For investigating the physical processes associated with generation of PD, a system for modelling, the study and analysis of physical phenomena associated with their generation in insulating oil were designed and implemented. In particular, the PD were simulated in three setups: (1) a surface system, (2) needle-needle system in insulating oil and (3) needle-needle system in insulating oil with gas bubbles. In these experimental setups, optical signals (IR, UV and visible), ultra–high frequency electromagnetic and highenergy X-ray radiation, acoustic emission and thermal images were registered. Record‐ ed signals were subjected for multi-variant investigation and analyses in the time and frequency domains. The contribution of particular physical phenomena was determined.

Frequency analysis of micro wind turbine vibrations using the MUSIC method

Analysis results of vibro-acoustic signals generated by operation of a micro wind turbine that is installed on the roof of Electric Power Institute, Opole University of Technology are presented in the paper. Mast vibrations of the turbine under study have been measured under different weather conditions, i.e. by various wind speeds. A frequency analysis by use of the MUSIC method was performed. Shown results depict changes of frequency components appearing in the spectrum of the measured signals.