Téléchargez le livre : Data-Driven Fault Detection for Industrial Processes

Data-Driven Fault Detection for Industrial Processes

Canonical Correlation Analysis and Projection Based Methods

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Éditeur :

Springer Vieweg


Paru le : 2017-01-02



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Description

Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.
Pages
112 pages
Collection
n.c
Parution
2017-01-02
Marque
Springer Vieweg
EAN papier
9783658167554
EAN PDF
9783658167561
Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
11
Taille du fichier
5079 Ko
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Prix
79,11 €

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