Folgen
Lianfang Cai
Lianfang Cai
Research Associate of Process Automation, Imperial College London
Bestätigte E-Mail-Adresse bei imperial.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Monitoring nonlinear and non-Gaussian processes using Gaussian mixture model-based weighted kernel independent component analysis
L Cai, X Tian, S Chen
IEEE transactions on neural networks and learning systems 28 (1), 122-135, 2015
1052015
A process monitoring method based on noisy independent component analysis
L Cai, X Tian, S Chen
Neurocomputing 127, 231-246, 2014
692014
Wide-Area Monitoring of Power Systems Using Principal Component Analysis and -Nearest Neighbor Analysis
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Transactions on Power Systems 33 (5), 4913-4923, 2018
642018
A new fault detection method for non-Gaussian process based on robust independent component analysis
L Cai, X Tian
Process Safety and Environmental Protection 92 (6), 645-658, 2014
622014
Real-Time Detection of Power System Disturbances Based on -Nearest Neighbor Analysis
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Access 5, 5631-5639, 2017
532017
Process fault detection based on dynamic kernel slow feature analysis
N Zhang, X Tian, L Cai, X Deng
Computers & Electrical Engineering 41, 9-17, 2015
462015
Noise-resistant joint diagonalization independent component analysis based process fault detection
X Tian, L Cai, S Chen
Neurocomputing 149, 652-666, 2015
272015
Nonlinear process fault diagnosis using kernel slow feature discriminant analysis
H Zhang, X Tian, L Cai
IFAC-PapersOnLine 48 (21), 607-612, 2015
182015
Multivariate detection of power system disturbances based on fourth order moment and singular value decomposition
L Cai, NF Thornhill, BC Pal
IEEE Transactions on Power Systems 32 (6), 4289-4297, 2017
172017
A local and global statistics pattern analysis method and its application to process fault identification
H Zhang, X Tian, X Deng, L Cai
Chinese Journal of Chemical Engineering 23 (11), 1782-1792, 2015
152015
A kernel time structure independent component analysis method for nonlinear process monitoring
L Cai, X Tian, N Zhang
Chinese Journal of Chemical Engineering 22 (11-12), 1243-1253, 2014
152014
Non-Gaussian process fault detection method based on modified KICA
CAI Lianfang, T Xuemin, Z Ni
CIESC Journal 63 (9), 2864, 2012
132012
A new process monitoring method based on noisy time structure independent component analysis
L Cai, X Tian
Chinese Journal of Chemical Engineering 23 (1), 162-172, 2015
122015
A blind seismic deconvolution method based on Particle Swarm Optimization
L Cai, X Tian
Progress in Geophysics 27 (3), 1116-1122, 2012
102012
A test model of a power grid with battery energy storage and wide-area monitoring
L Cai, NF Thornhill, S Kuenzel, BC Pal
IEEE Transactions on Power Systems 34 (1), 380-390, 2018
92018
Process fault detection method based on time structure independent component analysis and one-class support vector machine
L Cai, X Tian, H Zhang
IFAC-PapersOnLine 48 (21), 1198-1203, 2015
72015
A multi-index control performance assessment method based on historical prediction error covariance
L Shang, X Tian, L Cai
IFAC-PapersOnLine 50 (1), 13892-13897, 2017
62017
Nonlinear dynamic fault dignosis method based on dautoencoder
N Zhang, XM Tian, LF Cai
2013 Fifth International Conference on Measuring Technology and Mechatronics …, 2013
62013
Process fault detection method using time-structure KICA and OCSVM
L Cai, X Tian, N Zhang
Journal of Tsinghua University Science and Technology 52 (9), 2012
62012
Non-linear process fault detection method based on RISOMAP [J]
Z Ni, T Xuemin, C Lianfang
Journal of Chemical Industry Engineering 64 (06), 2125-2130, 2013
52013
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20