Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges K Tidriri, N Chatti, S Verron, T Tiplica Annual Reviews in Control 42, 63-81, 2016 | 388 | 2016 |
Fault detection and identification with a new feature selection based on mutual information S Verron, T Tiplica, A Kobi Journal of Process Control 18 (5), 479-490, 2008 | 184 | 2008 |
Fault detection and isolation of faults in a multivariate process with Bayesian network S Verron, J Li, T Tiplica Journal of Process Control 20 (8), 902-911, 2010 | 122 | 2010 |
Fault diagnosis of industrial systems by conditional Gaussian network including a distance rejection criterion S Verron, T Tiplica, A Kobi Engineering applications of artificial intelligence 23 (7), 1229-1235, 2010 | 62 | 2010 |
A generic framework for decision fusion in fault detection and diagnosis K Tidriri, T Tiplica, N Chatti, S Verron Engineering Applications of Artificial Intelligence 71, 73-86, 2018 | 53 | 2018 |
A single Bayesian network classifier for monitoring with unknown classes MA Atoui, A Cohen, S Verron, A Kobi Engineering Applications of Artificial Intelligence 85, 681-690, 2019 | 48 | 2019 |
Diagnostic et surveillance des processus complexes par réseaux bayésiens S Verron Université d'Angers, 2007 | 47 | 2007 |
A Bayesian network dealing with measurements and residuals for system monitoring MA Atoui, S Verron, A Kobi Transactions of the Institute of Measurement and Control 38 (4), 373-384, 2016 | 37 | 2016 |
Fault detection with conditional gaussian network MA Atoui, S Verron, A Kobi Engineering Applications of Artificial Intelligence 45, 473-481, 2015 | 28 | 2015 |
Fault diagnosis with bayesian networks: Application to the tennessee eastman process S Verron, T Tiplica, A Kobi 2006 IEEE international conference on industrial technology, 98-103, 2006 | 28 | 2006 |
Fault detection with bayesian network S Verron, T Tiplica, A Kobi Frontiers in Robotics, Automation and Control, 2008 | 27 | 2008 |
Model-based approach for fault diagnosis using set-membership formulation N Chatti, R Guyonneau, L Hardouin, S Verron, S Lagrange Engineering Applications of Artificial Intelligence 55, 307-319, 2016 | 23 | 2016 |
Multivariate control charts with a bayesian network S Verron, T Tiplica, A Kobi International Conference on Informatics in Control, Automation and Robotics …, 2007 | 23 | 2007 |
Fault Detection and Diagnosis in a Bayesian Network classifier incorporating probabilistic boundary1 MA Atoui, S Verron, A Kobi IFAC-PapersOnLine 48 (21), 670-675, 2015 | 22 | 2015 |
Identification of apple varieties using acoustic measurements T Tiplica, P Vandewalle, S Verron, C Grémy-Gros, E Mehinagic Conférence Internationale en Métrologie (CAFMET'10), 2010 | 22 | 2010 |
Model-based fault detection and diagnosis of complex chemical processes: A case study of the Tennessee Eastman process K Tidriri, N Chatti, S Verron, T Tiplica Proceedings of the Institution of Mechanical Engineers, Part I: Journal of …, 2018 | 16 | 2018 |
Procedure based on mutual information and bayesian networks for the fault diagnosis of industrial systems S Verron, T Tiplica, A Kobi 2007 American Control Conference, 420-425, 2007 | 14 | 2007 |
A decision fusion based methodology for fault Prognostic and Health Management of complex systems K Tidriri, S Verron, T Tiplica, N Chatti Applied Soft Computing 83, 105622, 2019 | 13 | 2019 |
Conditional gaussian network as pca for fault detection MA Atoui, S Verron, K Abdessamad IFAC Proceedings Volumes 47 (3), 1935-1940, 2014 | 11 | 2014 |
Monitoring of complex processes with Bayesian networks S Verron, T Tiplica, A Kobi Bayesian Network, 213-227, 2010 | 11 | 2010 |