img Leseprobe Leseprobe

Data-Driven Fault Detection for Industrial Processes

Canonical Correlation Analysis and Projection Based Methods

Zhiwen Chen

PDF
ca. 80,24 €
Amazon iTunes Thalia.de Weltbild.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Springer Fachmedien Wiesbaden img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik

Beschreibung

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.

Weitere Titel in dieser Kategorie
Cover ARDUINO DETECTION
ARDUINO DETECTION
ADDISON GARDNER
19,99 €

Kundenbewertungen

Schlagwörter

Kernel representation, Data-Driven method, Multivariate statistical process monitoring, Deterministic disturbances, Performance evaluation, Subspace method