This paper presents comparative analysis of various acoustic signals expected during partial discharge (PD) measurements in operating power transformer. Main purpose of the paper is to yield relevant and reliable method to distinguish between various acoustic emission (AE) signals emitted by PD and other sources, with particular consideration of real-life results rather than laboratory simulations. Therefore, selected examples of real-life AE signals registered in seven different power transformers, under normal operation conditions, within few years are showed and analyzed. Five scenarios are investigated, which represent five types of AE sources: PD generated by artificial sources, and next four real-life sources (including PD in working transformer, oil flow, oil pumps and core). Several different signal processing methods are applied and compared in order to identify the PD signals. As a result, an energy patterns analysis based on the wavelet decomposition is found as the most reliable tool for identification of PD signals. The presented results may significantly support the process of interpretation of the PD measurement results, and may be used by field engineers as well as other researchers involved in PD analysis using AE method. Finally, observed properties also provide a solid basis for establishing or improving complete classification method based on the artificial intelligence algorithms.

The main purpose of the presented research is to investigate the partial discharge (PD) phenomenon variability under long-term AC voltage with particular consideration of the selected physical quantities changes while measured and registered by the acoustic emission method (AE). During the research a PD model source generating surface discharges is immersed in the brand new insulation mineral oil. Acoustic signals generated by the continuously occurred PDs within 168 hours are registered. Several qualitative and quantitative indicators are assigned to describe the PD variability in time. Furthermore, some longterm characteristics of the applied PD model source in mineral oil, are also presented according to acoustic signals emitted by the PD. Finally, various statistical tools are applied for the results analysis and presentation. Despite there are numerous contemporary research papers dealing with long-term PD analysis, such complementary and multiparametric approach has not been presented so far, regarding the presented research. According to the presented research from among all assigned indicators there are discriminated descriptors that could depend on PD long-term duration. On the grounds of the regression models analysis there are discovered trends that potentially allow to apply the results for modeling of the PD variability in time using the acoustic emission method. Subsequently such an approach may potentially support the development and extend the abilities of the diagnostic tools and maintenance policy in electrical power industry.

The Bulletin of the Polish Academy of Sciences: Technical Sciences (Bull.Pol. Ac.: Tech.) is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics.

Journal Metrics: JCR Impact Factor 2018: 1.361, 5 Year Impact Factor: 1.323, SCImago Journal Rank (SJR) 2017: 0.319, Source Normalized Impact per Paper (SNIP) 2017: 1.005, CiteScore 2017: 1.27, The Polish Ministry of Science and Higher Education 2017: 25 points.

Abbreviations/Acronym: Journal citation: Bull. Pol. Ac.: Tech., ISO: Bull. Pol. Acad. Sci.-Tech. Sci., JCR Abbrev: B POL ACAD SCI-TECH Acronym in the Editorial System: BPASTS.

An alternative method for analysis of acoustic emission (AE) signals generated by partial discharges (PD), based on a correlation between voltage phase run and AE pulses, so called phase resolved PD pattern (PRPD), is presented in the paper. PRPD pattern is a well-known analysis tool commonly used in such PD diagnostic methods as conventional electrical and UHF ones. Moreover, it yields various signal analysis abilities and allows a direct correlation indication between measurement results achieved using different methods. An original PRPD measurement methodology applied for AE method as well as some exemplary measurement results and further data analysis capabilities are presented in the paper. Also a comparative analysis of PRPD patterns achieved using various measurement methods and different PD source configurations have been investigated. All presented experiments were done under laboratory conditions using PD model sources immersed in the insulation oil. The main purpose of the presented research is to indicate an all-embracing analytical tool that yields an ability to direct comparison (qualitative as well as quantitative) of the AE measurement results with other commonly applied PD measurement methods. The presented results give a solid fundamental for further research work concerning a direct correlation method for AE and other described in the paper diagnostic techniques, mainly in order to continue PD phenomena analysis and assessment in real life high voltage apparatus insulation systems under normal onsite operation conditions.

An acoustic emission method (AE) is widespread and often applied for partial discharge (PD) diagnostics, mainly due to its ease of application as well as noninvasiveness and relatively high sensitivity. This paper presents comparative analysis of AE signals measurement results archived under laboratory conditions as well as on-site actual AE signals generated by inside PDs in electrical power transformer during its normal service. Three different PD model sources are applied for laboratory research: point to point, multipoint to plate and surface type. A typical measuring set up commonly used for on-site transformer PD diagnostics is provided for the laboratory tasks: piezoelectric joint transducer, preamplifier, amplifier and measuring PC interface. During the on-site research there are three measuring tracks applied simultaneously. Time domain, time-frequency domain and statistical tools are used for registered AE signals analysis. A number of descriptors are proposed as a result of the analysis. In the paper, at- tempt of AE signals descriptors, archived under laboratory condition application possibilities for on-site PD diagnostics of power transformers during normal service is made.