Intelligent Data Analytics for Power Apparatus Health Monitoring: AI and Machine Learning Paradigms

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Hasmat Malik (Postdoctoral Scholar, BEARS, Singapore; Assistant Professor, Division of Instrumentation and Control Engineering, Netaji Subhas University of Technology, Delhi, India) Nuzhat Fatema (Singapore Polyclinic, Singapore; Research Associate, National Board of Examinations (NBE), India)

Intelligent Data Analytics for Power Apparatus Health Monitoring

AI and Machine Learning Paradigms

Hasmat Malik (Postdoctoral Scholar, BEARS, Singapore; Assistant Professor, Division of Instrumentation and Control Engineering, Netaji Subhas University of Technology, Delhi, India), Nuzhat Fatema (Singapore Polyclinic, Singapore; Research Associate, National Board of Examinations (NBE), India), Raj Kumar Jarial (Electrical Engineering Department, National Institute of Technology Hamirpur (H.P.), India) , Atif Iqbal (Full Professor, Department of Electrical Engineering, Qatar University; Former Professor, Electrical Engineering, Aligarh Muslim University (AMU), Qatar)

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English

Academic Press Inc
01 November 2024

Electrical engineering; Power generation & distribution; Data capture & analysis; Machine learning

Intelligent Data Analytics for Power Apparatus Health Monitoring: AI and Machine Learning Paradigms reviews key implementations of machine learning and data analytics techniques for the optimization of digital power transformers. The work addresses health monitoring fully across the constitutive structure of modern transformers, with coverage of DGA-based intelligent data analytics, transformer winding, bushing and arrestor health monitoring, core, conservator, and tank and cooling systems. Chapters address advanced AI/ML methods including deep convolutional neural network, fuzzy reinforcement learning, modified fuzzy Q learning, gene expression programming, extreme-learning machine, and much more.

Primarily intended for researchers and practitioners, the book speeds and simplifies the diagnosis and resolution of health and condition monitoring queries using advanced techniques, particularly with the goal of improved performance, reduced cost, optimized customer behavior and satisfaction, and ultimately increased profitability.

Edited by: Hasmat Malik (Postdoctoral Scholar BEARS Singapore; Assistant Professor Division of Instrumentation and Control Engineering Netaji Subhas University of Technology Delhi India), Nuzhat Fatema (Singapore Polyclinic, Singapore; Research Associate, National Board of Examinations (NBE), India), Raj Kumar Jarial (Electrical Engineering Department, National Institute of Technology Hamirpur (H.P.), India), Atif Iqbal (Full Professor, Department of Electrical Engineering, Qatar University; Former Professor, Electrical Engineering, Aligarh Muslim University (AMU), Qatar)
Imprint: Academic Press Inc
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 151mm,
ISBN: 9780323917797
ISBN 10: 0323917798
Pages: 276
Publication Date: 01 November 2024
Audience: Professional and scholarly , College/higher education , Undergraduate , Further / Higher Education
Format: Paperback
Publisher's Status: Active

Dr. Hasmat Malik received his Diploma in Electrical Engineering from Aryabhatt Govt. Polytechnic Delhi, B.Tech. degree in electrical & 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 systems from the 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 the Division of Instrumentation and Control Engineering, Netaji Subhas University of Technology Delhi, India. A member of various societies, Dr. Malik has published over 100 research articles, including papers in international journals, conferences, and book chapters. He was a Guest Editor of Special Issues of the Journal of Intelligent & Fuzzy Systems, in 2018 and 2020. Dr. Malik has supervised 23 postgraduate students and is involved in several large R&D projects. His principal research interests are artificial intelligence, machine learning, and big-data analytics for renewable energy, smart building & automation, condition monitoring, and online fault detection & diagnosis (FDD). Dr Nuzhat Fatema has 10 years of experience in Intelligent data analytics using AI & Machine learning for hospital and health care management. Dr. Fatema is the founder of the Intelligent-Prognostic (iPrognostic) Pvt. Ltd. Her area of interest is AI, ML and intelligent data analytics application in healthcare, monitoring, prediction, forecasting, detection and diagnosis to optimize decision-making in diagnosis, management and industry care. Dr Raj Kumar Jarial is an Associate Professor in the department of electrical engineering, Qatar University, Doha, Qatar. His principle research interests are power electronics applications in electrical drives, power systems, high voltage engineering, renewable energy, smart buildings and automation, condition monitoring and online fault detection and diagnosis (FDD) of power transformers and health monitoring systems. Atif Iqbal, is a Professor in Electrical Engineering, Qatar University. He publishes widely in power electronics, variable speed drives and renewable energy sources. Dr. Iqbal has co-authored more than 400 research papers and two books. His principal area of research interest is smart grids, complex energy transitions, active distribution networks, electric vehicles drivetrains, sustainable development and energy security, and distributed energy generation.