Geometric properties of partial least squares for process monitoring

From MaRDI portal
Publication:985292

DOI10.1016/j.automatica.2009.10.030zbMath1233.62208OpenAlexW2039839604MaRDI QIDQ985292

S. Joe Qin, Gang Li, Dong Hua Zhou

Publication date: 20 July 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2009.10.030



Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).


Related Items (15)

Quality-related fault detection using linear and nonlinear principal component regressionDirect projection to latent variable space for fault detectionA new data-driven process monitoring scheme for key performance indictors with application to hot strip mill processImproved key performance indicator-partial least squares method for nonlinear process fault detection based on just-in-time learningFault detection for industrial processesProcess monitoring using a generalized probabilistic linear latent variable modelAssessment of \(T^2\)- and \(Q\)-statistics for detecting additive and multiplicative faults in multivariate statistical process monitoringA novel dynamic non-Gaussian approach for quality-related fault diagnosis with application to the hot strip mill processFuzzy fault isolation using gradient information and quality criteria from system identification modelsMultimode process monitoring method based on multiblock projection nonnegative matrix factorizationQuality-relevant fault detection and diagnosis for hot strip mill process with multi-specification and multi-batch measurementsData-driven design of fault detection and isolation method for distributed homogeneous systemsA practical propagation path identification scheme for quality-related faults based on nonlinear dynamic latent variable model and partitioned Bayesian networkA key performance indicator-based fault detection scheme for marine diesel turbocharging systemsHybrid variable monitoring: an unsupervised process monitoring framework with binary and continuous variables



Cites Work


This page was built for publication: Geometric properties of partial least squares for process monitoring