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 non-destructive 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 high-energy X-ray radiation, acoustic emission and thermal images were registered. Recorded signals were subjected for multi-variant investigation and analyses in the time and frequency domains. The contribution of particular physical phenomena was determined

The possibilities of cooperation among family firms within a cluster environment

PURPOSE: The aim of the article is to analyze the potential for effective implementation of clusters in the context of family businesses operating in the Polish market.DESIGN/METHODOLOGY/APPROACH: The article seeks to address the question of whether and what are the possibilities of implementing clusters in the operations of Polish family firms. It investigates the factors contributing to the success or failure of cluster initiatives among family businesses. The hypothesis posited is that family firms in the Polish market operate in isolation, and exhibit limited willingness to collaborate, yet despite these constraints, they are capable of engaging in clusters as a solution to some of their market challenges. The research methodology comprised Computer-Assisted Telephone Interviews (CATI) and InDepth Interviews (IDI) conducted in 2023 on a representative sample of 448 family firms.FINDINGS: The article presents the results of research on family firms in Poland, focusing on their market situation, analysis of constraints, and opportunities for utilizing networks in the development of these enterprises. According to the research findings, the majority of family firms are not familiar with the cluster concept, but some have experience in operating within networks. Family firms demonstrate a weak willingness to collaborate with other entities, as they highly value their autonomy and independence. They are generally not interested in influencing regional strategy, workforce transfer, or collaboration with academic and research centers. Factors essential to the essence of clusters are rejected by these firms. Family firms attribute the failures of clusters to a lack of conviction in the cluster concept itself, top-down cluster stimulation, clusters emerging as a response to trends, lack of appropriate personnel, and a lack of communal action habits typical for clusters. Family firms recognize that access to markets, innovative technologies, and entrepreneurialism are the primary drivers of cluster success. However, the research results indicate that increased awareness of clustering stimulates actions that contribute to cluster success. Therefore, despite the family firms' distant approach to clusters, it is acknowledged that these firms need to be made aware of the necessity of forming clusters as a way out of isolation and focusing on their own activities. To this end, a cluster-building procedure tailored to family firms has been developed, as engaging in cluster collaboration can be an opportunity for the development of these firms. This has the potential for success because the pursuit of cost reduction is one of the main benefits of participating in a cluster, and family firms are interested in this aspect.PRACTICAL IMPLICATIONS: Current market trends, along with prevailing quality requirements, increase the significance of clusters in shaping growth and development processes based on a set of criteria grounded in sustainability attributes. Consequently, the analysis of cluster utilization not only becomes a topical research issue but also a practical tool supporting the enduring and sustainable development of these firms.ORIGINALITY/VALUE: While numerous studies have focused on family firms and their management, relatively few of these studies have addressed the potential application of clusters by family firms. The research undertaken has yielded insights into the clustering of family firms, identifying causes of failures as well as the benefits of collaboration, which may serve as a valuable source of information, utilized, among other contexts, in the decisionmaking process regarding engagement in long-term agreements. In this regard, the present article seeks to fill a gap in the realm of cluster formation by family firms.Publication was funded by the state budget under the program of the Polish Ministry of Education and Science called “Science for Society” project number NdS/545753/2022/2022, amount of funding 678 000,00 PLN total value of the project 754 000,00 PLN (Poland)peer-reviewe

Numerical simulation of micro-crack occurring in pipe made of stainless steel

Research works carried out regard to studies aiming at determination of the effect of cumulative duty operation on the development of micro-cracks in pipelines for transport of chemical substances. This paper presents results of computer simulations of a pipeline made of stainless steel. The model was investigated using the COMSOL Multiphysics environment. The object under study was divided into sub areas and then discretized according to the FEM method. The physico-chemical parameters of individual areas were defined based on measurement data. The main aim of research works was the modeling of acoustic emission wave, which is emitted in the vicinity of the tip of micro-crack as a result of its development. In order to solve the task, heterogeneity in the structure of the material, referred to damage/micro-crack, causing local stresses was assumed. The local stresses give rise to elastic waves, which propagate in the material in all directions. When the emission waves reach the boundaries of the pipe they are then transferred into acoustic waves and propagate in the surround air, until their natural attenuation. The numerical model takes into account the effect of high pressure (3.6 MPa) and negative temperature (-100̊C) of the gas, transported inside the pipe. The influence of changes of these values in the range of ± 20% on the obtained results was investigated. The main contribution of the works is the multiphysical simulation model of transportation pipe made of steel, coupling structural mechanics, thermal conductivity and acoustic waves

Study on the Influence of Measuring AE Sensor Type on the Effectiveness of OLTC Defect Classification

The principal objective of this study is to improve the diagnostics of power transformers, which are the key element of supplying electricity to consumers. On Load Tap Changer (OLTC), which is the object of research, the results of which are presented in this article, is one of the most important elements of these devices. The applied diagnostic method is the acoustic emission (AE) method, which has the main advantage over others, that it is considered as a non-destructive testing method. At present, there are many measuring devices and sensors used in the AE method, there are also some international standards, according to which, measurements should be performed. In the presented work, AE signals were measured in laboratory conditions with various OLTC defects being simulated. Five types of sensors were used for the measurement. The recorded signals were analyzed in the time and frequency domain and using discrete wavelet transformation. Based on the results obtained, sets of indicators were determined, which were used as features for an autonomous classification of the type of defect. Several types of learning algorithms from the group of supervised machine learning were considered in the research. The performance of individual classifiers was determined by several quality evaluation measures. As a result of the analyses, the type and characteristics of the most optimal algorithm to be used in the process of classification of the OLTC fault type were indicated, depending on the type of sensor with which AE signals were recorded

Investigating the Capability of PD-Type Recognition Based on UHF Signals Recorded with Different Antennas Using Supervised Machine Learning

The article presents research on the influence of the type of UHF antenna and the type of machine learning algorithm on the effectiveness of classification of partial discharges (PD) occurring in the insulation system of a power transformer. For this purpose, four antennas specially adapted to be installed in the transformer tank (UHF disk sensor, UHF drain valve sensor, planar inverted F-type antenna, Hilbert curve fractal antenna) and a reference log-periodic antenna were used in laboratory tests. During the research, the main types of PD, typical for oil-paper insulation, were generated, i.e., PD in oil, PD in oil wedge, PD in gas bubbles, surface discharges, and creeping sparks. For the registered UHF PD pulses, nine features in the frequency domain and four features in the wavelet domain were extracted. Then, the PD classification process was carried out with the use of selected methods of supervised machine learning. The study investigated the influence of the number and type of feature on the obtained classification results gained with the following machine-learning methods: decision tree, support vector machine, Bayes method, k-nearest neighbor, linear discriminant, and ensemble machine. As a result of the works carried out, it was found that the highest accuracies are gathered for the feature representing peak frequency using a decision tree, reaching values, depending on the type of antenna, from 89.7% to 100%, with an average of 96.8%. In addition, it was found that the MRMR method reduces the number of features from 13 to 1 while maintaining very high effectiveness. The broadband log-periodic antenna ensured the highest average efficiency (100%) in the PD classification. In the case of the tested antennas adapted to work in an energy transformer tank, the highest defect-recognition efficiency is provided by the UHF disk sensor (99.3%), and the lowest (89.7%) is by the UHF drain valve sensor

Identyfikacja sezonowości na rynku mieszkaniowym przy użyciu modelu X13-ARIMA-SEATS

Aim: In the conducted research, profiles of seasonality in the housing market were determined, which provided an opportunity to answer two fundamental questions: what is the nature of harmonic variation in the seasonality and periodicity of the studied components of the construction process? what parameters of the ARIMA model optimally describe the construction market? Methodology: In the conducted research, using the X13-ARIMA-SEATS model, seasonal decomposition was carried out in the various stages of the housing construction process. Results: The research process conducted to identify seasonal fluctuations in the housing construction market showed that harmonic fluctuation profiles can be identified on an annual basis. An analysis of seasonal fluctuations was carried out for each of the three stages of the housing construction process, while also checking how these profiles function for Poland in general, and for individual investors, and for those building apartments for sale or to rent. The study showed that the market for real estate development activity differs in its seasonal characteristics from that of individual investors. Implications and recommendations: The conclusions obtained from the research can provide support in the decision-making process, both from a macro and microeconomic perspective. Parameterisation of the occurring fluctuations, and taking them into account in the process of developing a forecast can provide decision-making rationale in the implementation of macroprudential and financial stability policies Originality/Value: A novelty is in the demonstration that the residential real estate market in Poland shows different seasonal parameters, divided into the market of individual investors and investors who build apartments for sale or rent.Cel: W przeprowadzonych badaniach wyznaczono profile sezonowości na rynku mieszkaniowym, co dało możliwość odpowiedzi na dwa zasadnicze pytania: Jaki charakter ma harmoniczna zmienność sezonowości i okresowości badanych składowych procesu budowlanego? Jakie parametry modelu ARIMA optymalnie opisują rynek budowlany? Metodyka: W przeprowadzonych badaniach, wykorzystując model X13-ARIMA-SEATS, dokonano dekompozycji sezonowej w poszczególnych etapach procesu budownictwa mieszkaniowego. Wyniki: Proces badawczy przeprowadzony w celu identyfikacji wahań sezonowych na rynku budownictwa mieszkaniowego wykazał, że można zidentyfikować harmoniczne profile wahań w ujęciu rocznym. Analizę wahań sezonowych przeprowadzono dla każdego z trzech etapów procesu budowy mieszkań, sprawdzając jednocześnie, jak profile te kształtują się dla Polski ogółem oraz dla inwestorów indywidualnych i budujących mieszkania na sprzedaż lub wynajem. Badanie wykazało, że rynek działalności deweloperskiej różni się charakterystyką sezonową od rynku inwestorów indywidualnych. Implikacje i rekomendacje: Wnioski uzyskane z badań mogą stanowić wsparcie w procesie podejmowania decyzji z perspektywy zarówno makro-, jak i mikroekonomicznej. Parametryzacja występujących wahań i uwzględnienie ich w procesie opracowywania prognozy może stanowić przesłankę decyzyjną w realizacji inwestycji deweloperskich. Oryginalność/Wartość: Nowością jest wykazanie, że rynek nieruchomości mieszkaniowych w Polsce charakteryzuje się różnymi parametrami sezonowymi w podziale na rynek inwestorów indywidualnych oraz inwestorów wznoszących mieszkania na sprzedaż lub wynajem

Application of Correlation Analysis for Assessment of Infrasound Signals Emission by Wind Turbines

The study reported in this paper is concerned with areas related to developing methods of measuring, processing and analyzing infrasound noise caused by operation of wind farms. The paper contains the results of the correlation analysis of infrasound signals generated by a wind turbine with a rated capacity of 2 MW recorded by three independent measurement setups comprising identical components and characterized by the same technical parameters. The measurements of infrasound signals utilized a dedicated measurement system called INFRA, which was developed and built by KFB ACOUSTICS Sp. z o.o. In particular, the scope of the paper includes the results of correlation analysis in the time domain, which was carried out using the autocovariance function separately for each of the three measuring setups. Moreover, the courses of the cross-correlation function were calculated separately for each of the potential combinations of infrasound range recorded by the three measuring setups. In the second stage, a correlation analysis of the recorded infrasound signals in the frequency domain was performed, using the coherence function. In the next step, infrasound signals recorded in three setups were subjected to time-frequency transformations. In this part, the waveforms of the scalograms were determined by means of continuous wavelet transform. Wavelet coherence waveforms were calculated in order to determine the level of the correlation of the obtained dependencies in the time-frequency domain. The summary contains the results derived from using correlation analysis methods in the time, frequency and time-frequency domains

Comparison of low frequency signals emitted by wind turbines of two different generator types

Paper presents results of comparative analysis of infrasound noise generated by wind turbines of two types: asynchronous type REPOWER MM92 with power equal to 2 MW and synchronous type Vensys 62 with power equal to 1.2 MW. Frequency spectra of sound pressure levels generated during operation by both turbines for exemplary chosen wind speed values are depicted. Within the shown spectra the resonant frequencies have been indicated, for which sound pressure variations over time are shown. Based on the achieved frequency spectra it was stated that in general the asynchronous type turbine produces lower pressure levels, which are less stable over time, and indicates higher pressure values around the resonant frequencies as compared to the synchronous type turbine. Also it was stated that the asynchronous type turbine is more influenced by the wind conditions and generates higher pressure values by higher wind speeds then the synchronous type turbine. The main contribution of this paper lies in indication that the type of wind turbine generator has significant impact on the level of infrasound noise emitted to the environment

Comparison of low frequency signals emitted by wind turbines of two different generator types

Paper presents results of comparative analysis of infrasound noise generated by wind turbines of two types: asynchronous type REPOWER MM92 with power equal to 2 MW and synchronous type Vensys 62 with power equal to 1.2 MW. Frequency spectra of sound pressure levels generated during operation by both turbines for exemplary chosen wind speed values are depicted. Within the shown spectra the resonant frequencies have been indicated, for which sound pressure variations over time are shown. Based on the achieved frequency spectra it was stated that in general the asynchronous type turbine produces lower pressure levels, which are less stable over time, and indicates higher pressure values around the resonant frequencies as compared to the synchronous type turbine. Also it was stated that the asynchronous type turbine is more influenced by the wind conditions and generates higher pressure values by higher wind speeds then the synchronous type turbine. The main contribution of this paper lies in indication that the type of wind turbine generator has significant impact on the level of infrasound noise emitted to the environment

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