Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Author:   Jing Wang ,  Jinglin Zhou ,  Xiaolu Chen
Publisher:   Springer
ISBN:  

9789811680465


Pages:   284
Publication Date:   30 April 2022
Format:   Paperback
Availability:   Available To Order   Availability explained
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Data-Driven Fault Detection and Reasoning for Industrial Monitoring


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Overview

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.

Full Product Details

Author:   Jing Wang ,  Jinglin Zhou ,  Xiaolu Chen
Publisher:   Springer
Imprint:   Springer
Dimensions:   Width: 15.60cm , Height: 1.50cm , Length: 23.40cm
Weight:   0.399kg
ISBN:  

9789811680465


ISBN 10:   9811680469
Pages:   284
Publication Date:   30 April 2022
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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