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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Bibliografski detalji
Glavni autor:	Wang, Jing (auth)
Daljnji autori:	Zhou, Jinglin (auth), Chen, Xiaolu (auth)
Format:	Elektronički Poglavlje knjige
Jezik:	engleski
Izdano:	Springer Nature 2022
Serija:	Intelligent Control and Learning Systems 3
Teme:	Robotics Artificial intelligence 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
Online pristup:	OAPEN Library: download the publication OAPEN Library: description of the publication
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Data-Driven Fault Detection and Reasoning for Industrial Monitoring od Wang, Jing, Zhou, Jinglin, Chen, Xiaolu

Izdano 2022

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Elektronički e-knjiga

Data-Driven Fault Detection and Reasoning for Industrial Monitoring od Wang, Jing

Izdano 2022

DOAB: download the publication
DOAB: description of the publication

Elektronički Poglavlje knjige

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

Data-Driven Fault Detection and Reasoning for Industrial Monitoring od Wang, Jing, Zhou, Jinglin, Chen, Xiaolu

Data-Driven Fault Detection and Reasoning for Industrial Monitoring od Wang, Jing

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