Jing Wang

(Author)

Data-Driven Fault Detection and Reasoning for Industrial Monitoring (2022)Hardcover - 2022, 4 January 2022

Data-Driven Fault Detection and Reasoning for Industrial Monitoring (2022)
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Part of Series
Intelligent Control and Learning Systems
Print Length
264 pages
Language
English
Publisher
Springer
Date Published
4 Jan 2022
ISBN-10
9811680434
ISBN-13
9789811680434

Description

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.

Product Details

Authors:
Jing WangJinglin ZhouXiaolu Chen
Book Edition:
2022
Book Format:
Hardcover
Country of Origin:
NL
Date Published:
4 January 2022
Dimensions:
23.39 x 15.6 x 1.75 cm
ISBN-10:
9811680434
ISBN-13:
9789811680434
Language:
English
Location:
Singapore
Pages:
264
Publisher:
Weight:
576.06 gm

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