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© 2020

Intelligent Condition Based Monitoring

For Turbines, Compressors, and Other Rotating Machines

Book

Part of the Studies in Systems, Decision and Control book series (SSDC, volume 256)

Table of contents

  1. Front Matter
    Pages i-xxx
  2. Nishchal K. Verma, Al Salour
    Pages 1-5
  3. Nishchal K. Verma, Al Salour
    Pages 7-88
  4. Nishchal K. Verma, Al Salour
    Pages 89-120
  5. Nishchal K. Verma, Al Salour
    Pages 121-173
  6. Nishchal K. Verma, Al Salour
    Pages 175-200
  7. Nishchal K. Verma, Al Salour
    Pages 201-224
  8. Nishchal K. Verma, Al Salour
    Pages 225-266
  9. Nishchal K. Verma, Al Salour
    Pages 267-281
  10. Nishchal K. Verma, Al Salour
    Pages 283-302

About this book

Introduction

This book discusses condition based monitoring of rotating machines using intelligent adaptive systems. The book employs computational intelligence and fuzzy control principles to deliver a module that can adaptively monitor and optimize machine health and performance. This book covers design and performance of such systems and provides case studies and data models for fault detection and diagnosis. The contents cover everything from optimal sensor positioning to fault diagnosis. The principles laid out in this book can be applied across rotating machinery such as turbines, compressors, and aircraft engines. The adaptive fault diagnostics systems presented can be used in multiple time and safety critical applications in domains such as aerospace, automotive, deep earth and deep water exploration, and energy.

 

 


Keywords

Intelligent Condition Based Monitoring Condition Based monitoring Fault Diagnosis Rotary Machines Model Based Fault Diagnosis Machine Health Monitoring Feature Extraction Rotating Machine Selection Rotating Machine Classification Smartphone Based Condition Monitoring

Authors and affiliations

  1. 1.Department of Electrical Engineering and Inter-disciplinary Program in Cognitive ScienceIndian Institute of Technology KanpurKanpurIndia
  2. 2.Boeing Research and TechnologySaint LouisUSA

About the authors

Dr. Nishchal K. Verma (SM'13) is a Professor in Department of Electrical Engineering and Inter-disciplinary Program in Cognitive Science at Indian Institute of Technology Kanpur, India. He obtained PhD in Electrical Engineering from Indian Institute of Technology Delhi, India. He is an awardee of Devendra Shukla Young Faculty Research Fellowship by Indian Institute of Technology Kanpur, India for year 2013-16.

His research interests include intelligent fault diagnosis systems, prognosis and health management, big data analysis, deep learning of neural and fuzzy networks, machine learning algorithms, computational intelligence, computer vision, brain computer/machine interface, intelligent informatics, soft-computing in modelling and control, internet of things/ cyber physical systems, and cognitive science. He has authored more than 200 research papers.

Dr. Verma is an IETE Fellow. He is currently serving as a Guest Editor of the IEEE Access: special section on “Advance in Prognostics and System Health Management”, an Editor of the IETE Technical Review Journal, an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Transactions of the Institute of Measurement and Control, U.K. and editorial board member for several journals and conferences.

Dr. Al Salour is a Boeing Technical Fellow and the enterprise leader for the Network Enabled Manufacturing technologies. He is responsible for systems approach to develop, integrate, and implement affordable sensor based manufacturing strategies and plans to provide real time data for factory systems and supplier networks. He is building a model for the current and future Boeing factories by streamlining and automating data management to reduce factory direct labour and overhead support and promote manufacturing as a competitive advantage.

Dr. Salour’s accomplishments include machine health monitoring integrations, asset tracking and RFID system installations; and safety systems for automated guided vehicles. Dr. Salour is the research investigator with national and international premiere universities and research labs. He serves as a committee vice chair for the ASME’s prognostics and health manaement national society. He is also a member of Industrial wireless technical working group with the National Institute of Standards and Technology (NIST). 

Dr. Salour has 31 invention disclosures, 22 patents and 1 trade secret in manufacturing technologies.

Bibliographic information

  • Book Title Intelligent Condition Based Monitoring
  • Book Subtitle For Turbines, Compressors, and Other Rotating Machines
  • Authors Nishchal K. Verma
    Al Salour
  • Series Title Studies in Systems, Decision and Control
  • Series Abbreviated Title Studies in Systems, Decision and Control
  • DOI https://doi.org/10.1007/978-981-15-0512-6
  • Copyright Information Springer Nature Singapore Pte Ltd. 2020
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-981-15-0511-9
  • Softcover ISBN 978-981-15-0514-0
  • eBook ISBN 978-981-15-0512-6
  • Series ISSN 2198-4182
  • Series E-ISSN 2198-4190
  • Edition Number 1
  • Number of Pages XXX, 302
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Machinery and Machine Elements
    Computational Intelligence
    Quality Control, Reliability, Safety and Risk
  • Buy this book on publisher's site
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