Paperback. This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The books goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes.The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field. This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Bibliographic Details

Title: Soft Computing in Condition Monitoring and Diagnostics of Electrical and Mechanical Systems (Paperback)
Publisher: Springer Verlag, Singapore, Singapore
Publication Date: 2021
Language: English
ISBN 10: 9811515344
ISBN 13: 9789811515347
Binding: Paperback
Condition: new

About this title

Synopsis

This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The book’s goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes.

The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field.

About the Author

Hasmat Malik (M'16) received Diploma in Electrical Engineering from Aryabhatt Govt. Polytechnic Delhi, B.Tech. degree in electrical and electronics engineering from the GGSIP University, Delhi, M.Tech. degree in electrical engineering from National Institute of Technology (NIT), Hamirpur, Himachal Pradesh, and Ph.D. in power system from Electrical Engineering Department, Indian Institute of Technology (IIT) Delhi, India. He is currently a Postdoctoral Scholar at BEARS, University Town, NUS Campus, Singapore, and an Assistant Professor (on leave) at Division of Instrumentation and Control Engineering, Netaji Subhas University of Technology, Delhi, India. He is a Life Member of Indian Society for Technical Education (ISTE), Institution of Electronics and Telecommunication Engineering (IETE), International Association of Engineers, Hong Kong (IAENG), International Society for Research and Development, London (ISRD), and Member of the Institute of Electrical and Electronics Engineers (IEEE), USA, and MIR Labs, Asia. He has published more than 100 research articles, including papers in international journals, conferences, and book chapters. He is a Guest Editor of Special Issue of Journal of Intelligent & Fuzzy Systems, 2018. (SCI, Impact Factor 2019:1.637), (IOS Press). He received the POSOCO Power System Award (PPSA-2017) for his Ph.D. work for research and innovation in the area of power system. He has received best research papers awards at IEEE INDICON-2015, and full registration fee at IEEE SSD-2012 (Germany). His principle areas of research interests are artificial intelligence, machine learning and big data analytics for smart building & automation, condition monitoring and online fault detection & diagnosis (FDD).

Atif Iqbal (M’9, SM’11) is Fellow IET (UK), Fellow IE (India) and Senior Member IEEE, Ph.D. (UK), Associate Editor of IEEE Access, Editor-in-Chief, I-manager’s journal of Electrical Engineering, Former Associate Editor of IEEE Transactions On Industry Application, Associate Professor at the Dept. Electrical Engineering, Qatar University, and Former Full Professor at the Dept. of Electrical Engineering, Aligarh Muslim University (AMU), Aligarh, India,. Recipient of Outstanding Faculty Merit Award AY 2014–2015 and Research Excellence Award 2015 and 2019, at Qatar University, Doha, Qatar. He received his B.Sc. (Gold Medal) and M.Sc. Engineering (Power System & Drives) degrees in 1991 and 1996, respectively, from the Aligarh Muslim University (AMU), Aligarh, India, and Ph.D. in 2006 from Liverpool John Moores University, Liverpool, UK. He has been employed as a Lecturer in the Department of Electrical Engineering, AMU, Aligarh, since 1991 where he served as the Full Professor until August 2016. He is recipient of Maulana Tufail Ahmad Gold Medal for standing first at B.Sc. Engg. Exams in 1991 from AMU. He has received best research papers awards at IEEE ICIT-2013, IET-SEISCON-2013, and SIGMA 2018. He has published widely in international journals and conferences his research findings related to Power Electronics, Motor Drives and Renewable Energy Sources. He has supervised several large R&D projects worth multi-million USD. He has supervised several PhDs. His principal areas of research interest are modeling and simulation of power electronic converters, control of multi-phase motor drives, Condition Monitoring of Motor Drives, Smart Grid, Active Distribution Network, Electric and Hybrid Electric Vehicles and Renewable energy sources.

Dr Amit Kumar Yadav received B.Tech. in Electrical and Electronics Engineering in 2009 from UCER Naini Allahabad U.P., India, M.Tech. in Power System in 2011 and Ph.D. in artificial neural network-based prediction of solar radiation for optimum sizing of photovoltaic systems for power generation in 2016 from Centre for Energy and Environmental Engineering National Institute of Technology, Hamirpur, Himachal Pradesh, India. Currently, he is an Assistant Professor in Electrical and Electronics Engineering Department, National Institute of Technology, Sikkim. His research interests include solar radiation and wind speed prediction for power generation, hybrid systems, artificial intelligence, optimization techniques and condition monitoring of power apparatus. He supervised more than 10 undergraduate projects and 1 M.Tech. projects. He is Editorial Board Member in Turkish Journal of Forecasting. He was awarded with “Research Ratna Awards 2019” for “Best Researcher In Solar Photovoltaic Systems For Maximum Power Generation” by Research Under Literal Access (RULA) International Awards. He has authored 11 science citation index international journals, 10 Scopus index international journals, 5 Springer and Elsevier book chapters and 12 IEEE Conference Publications. Most of the research papers are of impact factor 10.59. The h-index of research papers is 12, i-10 index is 14, and total citation ofpapers is more than 950.

He is reviewer of IET Science, Measurement & Technology, Neural Computing and Applications (Springer), Applied Energy (Elsevier), International Energy Journal, Electric Power Components and Systems Journal (Wiley), ISA Transactions (Elsevier), Sustainable Energy Technology and Assessment (Elsevier), Journal of Renewable and Sustainable Energy (American Institute of Physics), Jordanian Journal of Computers and Information Technology, IEEE Transaction on Industrial Electronics, International Journal of Electrical Power and Energy System (IJEP), Elsevier, Journal of Cleaner Production, Elsevier, Renewable and Sustainable Energy Review, Elsevier, Solar Energy Elsevier, Science and Technology for the Built Environment Taylor and Francis Journal.

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