| 1 |
Data-knowledge-driven diagnosis method for sludge bulking of wastewater treatment process
Han HG, Dong LX, Qiao JF
Journal of Process Control, 98, 106, 2021 |
| 2 |
Online reduced kernel GLRT technique for improved fault detection in photovoltaic systems
Fezai R, Mansouri M, Trabelsi M, Hajji M, Nounou H, Nounou M
Energy, 179, 1133, 2019 |
| 3 |
Monitoring of quality-relevant and quality-irrelevant blocks with characteristic-similar variables based on self-organizing map and kernel approaches
Yan SF, Huang JP, Yan XF
Journal of Process Control, 73, 103, 2019 |
| 4 |
A new dynamic integrated approach for wind speed forecasting
Sun SL, Qiao H, Wei YJ, Wang SY
Applied Energy, 197, 151, 2017 |
| 5 |
Combination of KPCA and causality analysis for root cause diagnosis of industrial process fault
Gharahbagheri H, Imtiaz S, Khan F
Canadian Journal of Chemical Engineering, 95(8), 1497, 2017 |
| 6 |
Efficient Monitoring of Nonlinear Chemical Processes based on Fault-Relevant Kernel Principal Component Subspace Construction and Bayesian Inference
Wang Y, Jiang QC, Fu JQ
Journal of Chemical Engineering of Japan, 50(8), 648, 2017 |
| 7 |
A novel acoustic emission detection module for leakage recognition in a gas pipeline valve
Li ZL, Zhang HF, Tan DJ, Chen X, Lei HX
Process Safety and Environmental Protection, 105, 32, 2017 |
| 8 |
Block adaptive kernel principal component analysis for nonlinear process monitoring
Xie L, Li Z, Zeng JS, Kruger U
AIChE Journal, 62(12), 4334, 2016 |
| 9 |
Multivariate time delay analysis based local KPCA fault prognosis approach for nonlinear processes
Xu Y, Liu Y, Zhu QX
Chinese Journal of Chemical Engineering, 24(10), 1413, 2016 |
| 10 |
Kernel PCA-based GLRT for nonlinear fault detection of chemical processes
Mansouri M, Nounou M, Nounou H, Karim N
Journal of Loss Prevention in The Process Industries, 40, 334, 2016 |
