SpringerBriefs in Applied Sciences and Technology

Capturing Connectivity and Causality in Complex Industrial Processes

Authors: Yang, F., Duan, P., Shah, S.L., Chen, T.

  • Provides an exhaustive overview of concepts and descriptions of connectivity and causality in complex processes
  • Explains how to obtain an acceptable process topology from the fusion of different information resources
  • Tutorial style deepens understanding of classical and recent research results with existing and potential applications
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eBook $39.99
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  • ISBN 978-3-319-05380-6
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Softcover $54.99
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  • ISBN 978-3-319-05379-0
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About this book

This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways:

·      from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and

·      from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian networks can be used to identify pair-wise relationships and network topology.

These methods rely on the notion of information fusion whereby process operating data is combined with qualitative process knowledge, to give a holistic picture of the system.

About the authors

The authors jointly have extensive research experience in modeling, control, and monitoring of complex industrial processes. In particular, they have worked on industrial projects in oil and petrochemical sectors to address safety, alarm, and fault diagnosis issues from operating plants. Moreover, they have conducted research in the related areas on capturing connectivity and causality using process data and various forms of process knowledge; their research results have been published in international journals, benefiting the automation community. Realizing the importance of capturing connectivity and causality in real-world problems, and summarizing their knowledge and understanding on various approaches currently available, the authors have made a great effort in presenting this brief as an introduction, a survey, and also a tutorial on this seasoned topic.

Table of contents (6 chapters)

  • Introduction

    Yang, Fan (et al.)

    Pages 1-6

  • Examples of Applications for Connectivity and Causality Analysis

    Yang, Fan (et al.)

    Pages 7-11

  • Description of Connectivity and Causality

    Yang, Fan (et al.)

    Pages 13-22

  • Capturing Connectivity and Causality from Process Knowledge

    Yang, Fan (et al.)

    Pages 23-39

  • Capturing Causality from Process Data

    Yang, Fan (et al.)

    Pages 41-65

Buy this book

eBook $39.99
price for USA (gross)
  • ISBN 978-3-319-05380-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $54.99
price for USA
  • ISBN 978-3-319-05379-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Capturing Connectivity and Causality in Complex Industrial Processes
Authors
Series Title
SpringerBriefs in Applied Sciences and Technology
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
The Author(s)
eBook ISBN
978-3-319-05380-6
DOI
10.1007/978-3-319-05380-6
Softcover ISBN
978-3-319-05379-0
Series ISSN
2191-530X
Edition Number
1
Number of Pages
XIII, 91
Number of Illustrations and Tables
30 b/w illustrations, 24 illustrations in colour
Topics