Uwe Kruger
TitleCited byYear
Principal manifolds for data visualization and dimension reduction
AN Gorban, B Kégl, DC Wunsch, AY Zinovyev
Springer 58, 96-130, 2008
Process monitoring approach using fast moving window PCA
X Wang, U Kruger, GW Irwin
Industrial & Engineering Chemistry Research 44 (15), 5691-5702, 2005
Recursive partial least squares algorithms for monitoring complex industrial processes
X Wang, U Kruger, B Lennox
Control Engineering Practice 11 (6), 613-632, 2003
Moving window kernel PCA for adaptive monitoring of nonlinear processes
X Liu, U Kruger, T Littler, L Xie, S Wang
Chemometrics and intelligent laboratory systems 96 (2), 132-143, 2009
Statistical Monitoring of Complex Multivatiate Processes: With Applications in Industrial Process Control
U Kruger, L Xie
John Wiley & Sons, 2012
Detection of incipient tooth defect in helical gears using multivariate statistics
N Baydar, Q Chen, A Ball, U Kruger
Mechanical systems and signal processing 15 (2), 303-321, 2001
Statistical‐based monitoring of multivariate non‐Gaussian systems
X Liu, L Xie, U Kruger, T Littler, S Wang
AIChE journal 54 (9), 2379-2391, 2008
Diagnosis of process faults in chemical systems using a local partial least squares approach
U Kruger, G Dimitriadis
AIChE Journal 54 (10), 2581-2596, 2008
Synthesis of T2 and Q statistics for process monitoring
Q Chen, U Kruger, M Meronk, AYT Leung
Control Engineering Practice 12 (6), 745-755, 2004
Improved principal component monitoring of large-scale processes
U Kruger, Y Zhou, GW Irwin
Journal of Process Control 14 (8), 879-888, 2004
Nonlinear PCA with the local approach for diesel engine fault detection and diagnosis
X Wang, U Kruger, GW Irwin, G McCullough, N McDowell
IEEE Transactions on Control Systems Technology 16 (1), 122-129, 2007
Improved principal component monitoring using the local approach
U Kruger, S Kumar, T Littler
Automatica 43 (9), 1532-1542, 2007
Extended PLS approach for enhanced condition monitoring of industrial processes
U Kruger, Q Chen, DJ Sandoz, RC McFarlane
AIChE journal 47 (9), 2076-2091, 2001
Dynamic multivariate statistical process control using subspace identification
RJ Treasure, U Kruger, JE Cooper
Journal of Process Control 14 (3), 279-292, 2004
Multivariate statistical process monitors
U Kruger, Q Chen, DJ Sandoz
US Patent 7,062,417, 2006
Regularised kernel density estimation for clustered process data
Q Chen, U Kruger, ATY Leung
Control Engineering Practice 12 (3), 267-274, 2004
Cointegration testing method for monitoring nonstationary processes
Q Chen, U Kruger, AYT Leung
Industrial & Engineering Chemistry Research 48 (7), 3533-3543, 2009
Improved reliability in diagnosing faults using multivariate statistics
D Lieftucht, U Kruger, GW Irwin
Computers & chemical engineering 30 (5), 901-912, 2006
Modeling and performance monitoring of multivariate multimodal processes
T Feital, U Kruger, J Dutra, JC Pinto, EL Lima
AIChE Journal 59 (5), 1557-1569, 2013
Developments and applications of nonlinear principal component analysis–a review
U Kruger, J Zhang, L Xie
Principal manifolds for data visualization and dimension reduction, 1-43, 2008
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Articles 1–20