This book offers an overview of current methods for the intelligent monitoring of rotating machines. It describes the foundations of smart monitoring, guiding readers to develop appropriate machine learning and statistical models for answering important challenges, such as the management and analysis of a large volume of data. It also discusses real-world case studies, highlighting some practical issues and proposing solutions to them. The book offers extensive information on research trends, and innovative strategies to solve emerging, practical issues. It addresses both academics and professionals dealing with condition monitoring, and mechanical and production engineering issues, in the era of industry 4.0.

"A first edition of Condition Monitoring of Electrical Machines, written by Tavner and Penman, was published in 1987. The economics of industry have now changed, as a result of the privatisation and deregulation of the energy industry, placing emphasis on the importance of reliable operation of plant, throughout the whole life cycle, regardless of first cost. The availability of advanced electronics and software in powerful instrumentation, computers, and digital signal processors (DSP) has simplified our ability to instrument and analyse machinery. As a result condition monitoring is now being applied to a wider range of systems from fault-tolerant drives of a few hundred watts in the aerospace industry, to machinery of a few hundred megawatts in major capital plant." "In this new book the original authors have been joined by Ran, an expert in power electronics and control, and Sedding, an expert in the monitoring of electrical insulation systems. Together the authors have revised and expanded the earlier book, merging their own experience with that of machine analysts to bring it up to date."--BOOK JACKET.

Condition monitoring of engineering plants has increased in importance as engineering processes have become increasingly automated. However, electrical machinery usually receives attention only at infrequent intervals when the plant or the electricity generator is shut down. The economics of industry have been changing, placing ever more emphasis on the importance of reliable operation of the plants. Electronics and software in instrumentation, computers, and digital signal processors have improved our ability to analyse machinery online. Condition monitoring is now being applied to a range of systems from fault-tolerant drives of a few hundred watts to machinery of a few hundred MW in major plants.

Rotating Machinery, Structural Health Monitoring, Shock and Vibration, Volume 5 Proceedings of the 29th IMAC, A Conference and Exposition on Structural Dynamics, 2011, the fifth volume of six from the Conference, brings together 35 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Rotating Machinery, Structural Health Monitoring, as well as Shock and Vibration, along with other structural engineering areas.

Industry 4.0 refers to fourth generation of industrial activity characterized by smart systems and internet-based solutions. This book describes the fourth revolution based on instrumented, interconnected and intelligent assets. The different book chapters provide a perspective on technologies and methodologies developed and deployed leading to this concept. With an aim to increase performance, productivity and flexibility, major application area of maintenance through smart system has been discussed in detail. Applicability of 4.0 in transportation, energy and infrastructure is explored, with effects on technology, organisation and operations from a systems perspective.

This book features high-quality research papers presented at Third Doctoral Symposium on Computational Intelligence (DoSCI 2022), organized by Institute of Engineering and Technology (IET), AKTU, Lucknow, India, on March 5, 2022. This book discusses the topics such as computational intelligence, artificial intelligence, deep learning, evolutionary algorithms, swarm intelligence, fuzzy sets and vague sets, rough set theoretic approaches, quantum inspired computational intelligence, hybrid computational intelligence, machine learning, computer vision, soft computing, distributed computing, parallel and grid computing, cloud computing, high performance computing, biomedical computing, and decision support and decision making.