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Data-Driven Fault Detection and Reasoning for Industrial Monitoring

84,68 
84,68 
2025-07-31 84.6800 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

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.

Informacija

Autorius: Jing Wang, Xiaolu Chen, Jinglin Zhou,
Serija: Intelligent Control and Learning Systems
Leidėjas: Springer Nature Singapore
Išleidimo metai: 2022
Knygos puslapių skaičius: 284
ISBN-10: 9811680434
ISBN-13: 9789811680434
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Automatic control engineering

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