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Data-Driven Fault Detection and Reasoning for Industrial Monitoring

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datacite.subject.fos oecd::Engineering and technology
dc.contributor.author Jing Wang, Jinglin Zhou, Xiaolu Chen
dc.date.accessioned 2023-06-17T01:42:26Z
dc.date.available 2023-06-17T01:42:26Z
dc.date.issued 2022
dc.description DOI: https://doi.org/10.1007/978-981-16-8044-1 License: CC BY; Publisher: Springer
dc.description.abstract "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." This work is licensed under a CC BY
dc.identifier.doi https://doi.org/10.1007/978-981-16-8044-1
dc.identifier.isbn 9789811680441
dc.identifier.uri http://repository.vlu.edu.vn:443/handle/123456789/5539
dc.language.iso en
dc.subject "Multivariate causality analysis
dc.subject Process monitoring
dc.subject Manifold learning
dc.subject Fault diagnosis
dc.subject Data modeling
dc.subject Fault classification
dc.subject Fault reasoning
dc.subject Causal network
dc.subject Probabilistic graphical model
dc.subject Data-driven methods
dc.subject Industrial monitoring
dc.subject Open Access."
dc.title Data-Driven Fault Detection and Reasoning for Industrial Monitoring
dc.type Resource Types::text::book
dspace.entity.type Publication
oairecerif.author.affiliation #PLACEHOLDER_PARENT_METADATA_VALUE#
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