Data-Driven Fault Detection for Industrial Processes

Name: Data-Driven Fault Detection for Industrial Processes
Brand: Springer Fachmedien Wiesbaden
SKU: 9783658167554
Price: 450.82 RON
Availability: InStock

Canonical Correlation Analysis and Projection Based Methods

Autor: Zhiwen Chen

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Editura: Springer Fachmedien Wiesbaden

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Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial p...

Informații despre carte

Autor

Zhiwen Chen

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2017

Pagini

112

EAN

9783658167554

ISBN

3658167556

Enbook ID

15497388

Editura

Springer Fachmedien Wiesbaden

Greutate

1806

Dimensiuni

148 x 210 x 8

Descriere completă

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.

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Data-Driven Fault Detection for Industrial Processes

Canonical Correlation Analysis and Projection Based Methods

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Descriere completă

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