Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Intelligent Reliability and Maintainability of Energy Infrastructure Assets

  • Book
  • © 2023

Overview

Authors:
  1. He Li

    1. Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto SuperiorTécnico, Universidade de Lisboa, Lisbon, Portugal

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Weiwen Peng

    1. School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  3. Sidum Adumene

    1. School of Ocean Technology, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John’s, Canada

    View author publications

    You can also search for this author in PubMed   Google Scholar

  4. Mohammad Yazdi

    1. Faculty of Science and Engineering, Macquarie University, Sydney, Australia

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Provides a clear overview of reliability and maintainability of energy infrastructure assets
  • Shows the reader a successful application of intelligent reliability and maintainability of energy infrastructure assets
  • Appeals to researchers, reliability and maintainability experts, and alike

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 473)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

eBook USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 159.99
Price excludes VAT (USA)
This title has not yet been released. You may pre-order it now and we will ship your order when it is published on 16 May 2024.
  • Compact, lightweight edition
  • Free shipping worldwide - see info
Hardcover Book USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains.

The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more.

This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.

Similar content being viewed by others

Keywords

Table of contents (9 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 1-23

  3. Cutting Edge Research Topics on System Safety, Reliability, Maintainability, and Resilience of Energy-Critical Infrastructures

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 25-38

  4. Operations Management of Critical Energy Infrastructure: A Sustainable Approach

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 39-52

  5. An Improved LeNet-5 Convolutional Neural Network Supporting Condition-Based Maintenance and Fault Diagnosis of Bearings

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 53-71

  6. Using Global Average Pooling Convolutional Siamese Networks for Fault Diagnosis of Planetary Gearboxes

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 73-91

  7. Advances in Failure Prediction of Subsea Components Considering Complex Dependencies

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 93-105

  8. An Intelligent Cost-Based Consequence Model for Offshore Systems in Harsh Environments

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 107-117

  9. A Sustainable Circular Economy in Energy Infrastructure: Application of Supercritical Water Gasification System

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 119-135

  10. Attention Towards Energy Infrastructures: Challenges and Solutions

    • He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi
    Pages 137-148
Back to top

Authors and Affiliations

  • Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto SuperiorTécnico, Universidade de Lisboa, Lisbon, Portugal

    He Li

  • School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China

    Weiwen Peng

  • School of Ocean Technology, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John’s, Canada

    Sidum Adumene

  • Faculty of Science and Engineering, Macquarie University, Sydney, Australia

    Mohammad Yazdi

Bibliographic Information

  • Book Title: Intelligent Reliability and Maintainability of Energy Infrastructure Assets

  • Authors: He Li, Weiwen Peng, Sidum Adumene, Mohammad Yazdi

  • Series Title: Studies in Systems, Decision and Control

  • DOI: https://doi.org/10.1007/978-3-031-29962-9

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-29961-2Published: 04 May 2023

  • Softcover ISBN: 978-3-031-29964-3Published: 05 May 2024

  • eBook ISBN: 978-3-031-29962-9Published: 03 May 2023

  • Series ISSN: 2198-4182

  • Series E-ISSN: 2198-4190

  • Edition Number: 1

  • Number of Pages: XIII, 148

  • Number of Illustrations: 2 b/w illustrations, 53 illustrations in colour

  • Topics: Computational Intelligence, Industrial and Production Engineering

Publish with us

Policies and ethics

Back to top

Search

Navigation