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Data-Driven Fault Detection and Reasoning for Industrial Monitoring

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 proce...

詳細記述

保存先:
主要な著者: Wang, Jing, Zhou, Jinglin, Chen, Xiaolu
フォーマット: Online
言語:英語
出版事項: Springer Nature 2022
主題:
Multivariate causality analysis
Process monitoring
Manifold learning
Fault diagnosis
Data modeling
Fault classification
Fault reasoning
Causal network
Probabilistic graphical model
Data-driven methods
Industrial monitoring
Open Access
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering::TJFM1 Robotics
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
オンライン･アクセス:ONIX_20220114_9789811680441_39
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要約: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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