Data-Driven Fault Detection and Reasoning for Industrial Monitoring (Hardcover, 1st ed. 2022)

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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.

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Product 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.

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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

Intelligent Control and Learning Systems, 3

Release date

2022

Availability

Expected to ship within 10 - 15 working days

First published

2022

Authors

, ,

Dimensions

235 x 155 x 25mm (L x W x T)

Format

Hardcover

Pages

264

Edition

1st ed. 2022

ISBN-13

978-981-16-8043-4

Barcode

9789811680434

Categories

LSN

981-16-8043-4



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