2014 |
Aribi, Asma; Farges, Christophe; Aoun, Mohamed; Melchior, Pierre; Najar, Slaheddine; Abdelkrim, Mohamed Naceur Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). Résumé | Liens | BibTeX | Étiquettes: Computer simulation, Diagnosis, Diagnosis methods, Fault detection, Fractional model, Fractional operators, Fractional order models, Numerical analysis, Reduced precision, Single input multi outputs, Thermal phenomena, Thermal systems @article{Aribi20143679b,The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagnosis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems. © 2014 Elsevier B.V. |
Aribi, Asma; Farges, Christophe; Aoun, Mohamed; Melchior, Pierre; Najar, Slaheddine; Abdelkrim, Mohamed Naceur Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). Résumé | Liens | BibTeX | Étiquettes: Computer simulation, Diagnosis, Diagnosis methods, Fault detection, Fractional model, Fractional operators, Fractional order models, Numerical analysis, Reduced precision, Single input multi outputs, Thermal phenomena, Thermal systems @article{Aribi20143679,The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagnosis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems. © 2014 Elsevier B.V. |
Publications
2014 |
Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). |
Fault detection based on fractional order models: Application to diagnosis of thermal systems Article de journal Dans: Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 10, p. 3679 – 3693, 2014, (Cited by: 28). |