Large‐scale dynamic process monitoring based on performance‐driven distributed canonical variate analysis
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3192
Abstract: As a typical process monitoring method for the large‐scale industrial process, the distributed principal components analysis (DPCA) needs to be improved because of its rough selection for the variables in each subblock. Moreover, for DPCA,… read more here.
Keywords: variate analysis; analysis; canonical variate; process ... See more keywords
Enhancing Canonical Variate Analysis by taking the scaling effect into account
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DOI: 10.1016/j.foodqual.2017.10.019
Abstract: Abstract Sensory profiling aims to describe the sensory characteristics of food products using a list of descriptors with a panel of trained assessors. During sensory evaluations (or any other scoring task), individual differences in the… read more here.
Keywords: cva; variate analysis; scaling effect; canonical variate ... See more keywords
Fault detection of process correlation structure using canonical variate analysis-based correlation features
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DOI: 10.1016/j.jprocont.2017.09.003
Abstract: Abstract This paper proposes a canonical variate analysis (CVA) approach based on feature representation of canonical correlation for the monitoring of faults associated with changes in process correlations, which involves two new metrics, R s… read more here.
Keywords: variate analysis; canonical correlation; canonical variate; correlation ... See more keywords
Sparse canonical variate analysis approach for process monitoring
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DOI: 10.1016/j.jprocont.2018.09.009
Abstract: Abstract Canonical variate analysis (CVA) has shown its superior performance in statistical process monitoring due to its effectiveness in handling high-dimensional, serially, and cross-correlated dynamic data. A restrictive condition for CVA is that the covariance… read more here.
Keywords: canonical variate; process; variate analysis; process monitoring ... See more keywords
Enhanced canonical variate analysis with slow feature for dynamic process status analytics
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Process Control"
DOI: 10.1016/j.jprocont.2020.09.005
Abstract: Abstract Process dynamics is widely presented in industrial processes, which can be perceived as temporal correlations. Negligence of dynamic information may result in misleading monitoring results. Therefore, explicit exploration of dynamic information is crucial to… read more here.
Keywords: variate analysis; enhanced canonical; process; canonical variate ... See more keywords