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...

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Bibliographic Details

Main Authors:	Wang, Jing, Zhou, Jinglin, Chen, Xiaolu
Format:	Online
Language:	English
Published:	Springer Nature 2022
Subjects:	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
Online Access:	ONIX_20220114_9789811680441_39
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