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Books > Professional & Technical > Industrial chemistry & manufacturing technologies
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Data-Driven Fault Detection for Industrial Processes - Canonical Correlation Analysis and Projection Based Methods (Paperback, 1st ed. 2017)
Loot Price: R1,581
Discovery Miles 15 810
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Data-Driven Fault Detection for Industrial Processes - Canonical Correlation Analysis and Projection Based Methods (Paperback, 1st ed. 2017)
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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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