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Power quality analysis in electrical drives and a case study of artificial intelligence prediction algorithm for fault deterrent electrical drives

Object's details: Power quality analysis in electrical drives and a case study of artificial intelligence prediction algorithm for fault deterrent electrical drives

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Provider:Czasopisma PAN

Description

Title:
Power quality analysis in electrical drives and a case study of artificial intelligence prediction algorithm for fault deterrent electrical drives
Creator:
K., Vishnu Murthy;
L., Ashok Kumar
Contributor:
K., Vishnu Murthy : Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, Tamilnadu, India;
L., Ashok Kumar : Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, Tamilnadu, India
Description:
The Bulletin of the Polish Academy of Sciences Technical Sciences 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. Submit your article Journal Metrics: JCR Impact Factor 2023: 1.2 5 Year Impact Factor 2022: 1.1 CiteScore 2023: 2.8 SCImago Journal Rank (SJR) 2023: 0.282 Source Normalized Impact per Paper (SNIP) 2023: 0.573 Ministry of Education and Science: 100 points Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.;
Editorial Board 2023-2025 Editor-in-Chief: A. Rogalski, Military University of Technology Honorary (Past) Editor-in Chief: T. Kaczorek, Warsaw University of Technology M.P. Kaźmierkowski, Warsaw University of Technology Deputy Editor-in-Chief: B. Błachowski, Institute of Fundamental Technological Research PAN M. Mrozowski, Gdansk University of Technology Board of Topical Co-editors: Artificial and Computational Intelligence S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology Biomedical Engineering and Biotechnology D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN Civil Engineering L. Czarnecki, Building Research Institute, ITB, Warsaw Ł. Sadowski, Wroclaw University of Science and Technology Control, Robotics and Informatics J. Klamka and A. Babiarz, Silesian Technical University J. Stefanowski, Poznan University of Technology Electronics, Telecommunication and Optoelectronics M. Mrozowski and A. Lamęcki, Gdansk University of Technology Mechanical and Aeronautical Engineering, Thermodynamics B. Błachowski, Institute of Fundamental Technological Research PAN G. Zboiński, Institute of Fluid-Flow Machinery PAN and University of Warmia and Mazury in Olsztyn Materials Science and Nanotechnology B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN Power Systems and Power Electronics J. Rąbkowski and M. Jasiński, Warsaw University of Technology International Editorial Advisory Board R. Asthana, University of Wisconsin-Stout, Menomonie, USA Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China F. Blaabjerg, Aalborg University, Denmark C. Cecati, University of L’Aquila, Italy A. Cichocki, RIKEN Institute, Tokyo, Japan M. David, National Polytechnique de Toulouse, France R. Ebner, Materials Centre Leoben, Leoben, Austria E. Fornasini, University of Padova, Padova, Italy L.G. Franquelo, University of Sevilla, Spain M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA M. Giersig, Free University of Berlin, Germany D. van Gemert, Catholic University Leuven, KU Leuven, Belgium L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary V. Kučera, Czech Technical University in Prague, Prague, Czech Republic R. Kennel, Technical University Munich, Germany T.A. Kowalewski, Institute of Fundamental Technological Research PAN E. Levi, Liverpool John Moore University, UK G. Maier, Technical University of Milan, Milan, Italy K.F. Man, City University of Hong Kong, R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN H.A. Mang, Austrian Academy of Sciences, Vienna, Austria H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan S. Mindess, University of British Columbia, Vancouver, Canada D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany A.S. Nowak, University of Michigan, Ann Arbor, USA K. Ohnishi, Keio University, Yokohama, Japan A. Öberg, Linköping University, Linköping, Sweden W. Pedrycz, University of Alberta, Canada M. Razeghi, Northwestern University, Evanston, USA J. Rodriguez, University of Andres Bello, Santiago, Chile J.V. Sloten, Catholic University Leuven, Leuven, Belgium B.M. Wilamowski, University of Auburn, Alabama, USA A.L. Yarin, University of Illinois at Chicago, USA Du Xiangwan, Chinese Academy of Engineering, China J. Żurada, Department of Computer Engineering, University of Louisville, USA;
NEW PUBLICATION FEES Articles submitted by December 31st, 2024: existing fee: 1500 PLN (and mandatory over-length charges of 230 PLN per page) Articles submitted from January 1st, 2025: new fee: 2000 PLN (approx. 500 EUR- depending on the exchange rate) - a flat fee per paper up to 8 pages of the journal format (each additional page will be charged an additional 250 PLN).
Object availability:
free access
Rights:
Bulletin of the Polish Academy of Sciences Technical Sciences jest czasopismem wydawanym w wolnym dostępie na licencji CC BY 4.0. </span></p>
Date:
2022.05.23
Type:
Article
Coverage:
e141180
Subject:
voltage sag/swell;
voltage imbalance;
machine learning;
inverter drives;
artificial intelligence
Identifier:
e-ISSN 2300-1917
Data provider:
Czasopisma PAN

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Power quality analysis in electrical drives and a case study of artificial intelligence prediction algorithm for fault deterrent electrical drives

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