Equipment Health Monitoring in Complex Systems

Equipment Health Monitoring in Complex Systems

Copyright: 2017
 Pages: 250
 ISBN: 9781630814977
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Description

This timely resource provides a practical introduction to equipment health monitoring (EHM) to ensure the cost effective operation and control of critical systems in defense, industrial, and healthcare applications. This book highlights how to frame health monitoring design applications within a system engineering process, to ensure an optimized EHM functional architecture and practical algorithm design.

 

This book clarifies the need for intelligent diagnostics and proposed health monitoring framework. Machine learning for health monitoring, including feature extraction, data visualization, model boundaries and performance is presented. Details about monitoring aircraft engines and model based monitoring systems are described in detail. Packed with two full chapters of case studies within industrial and healthcare settings, this book identifies key problems and provides insightful techniques for solving them. This resource provides a look into the future direction in health monitoring and emerging developments within sensing technology, big data analytics, and advanced computing capabilities.
Table Of Contents

Systems Engineering for EHM; The Need for Intelligent Diagnostics; Machine Learning for Health Monitoring; Case Studies of Medical Monitoring Systems; Monitoring Aircraft Engines; Future Directions in Health Monitoring

Author

  • Stephen P. King

    is an engineering associate fellow and equipment health management specialist at Rolls-Royce Digital Business. He is also a visiting professor at Cranfield University. He received his Ph.D. in mathematics and computer science from Lancaster University.

  • Andrew R. Mills

    is a senior research fellow and program manager for the Rolls-Royce University Technology Center. He received his Ph.D. and M.Eng. in control system engineering from the University of Sheffield.

  • Visakan Kadirkamanathan

    is a professor of signal and information processing at Cambridge University. He is also the director of the Rolls-Royce University Technology Center for Control and Monitoring Systems Engineering at Sheffield University. He received his Ph.D. in information engineering and his B.A. in electrical and information sciences at Cambridge University.

  • Dave A. Clifton

    is an associate professor in the Department of Engineering Science at the University of Oxford and a governing body fellow of Balliol College, Oxford. He is a research fello of the Royal Academy of Engineering and leads the Computational Health Informatics (CHI) laboratory. He received his Ph.D. in information engineering at the University of Oxford.