Documents disponibles écrits par cet auteur

Effect of manipulated variables selection on the controllability of chemical processes / Zhihong Yuan in Industrial & engineering chemistry research, Vol. 50 N° 12 (Juin 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 12 (Juin 2011) . - pp. 7403-7413 Titre : Effect of manipulated variables selection on the controllability of chemical processes Type de document : texte imprimé Auteurs : Zhihong Yuan, Auteur ; Bingzhen Chen, Auteur ; Jinsong Zhao, Auteur Année de publication : 2011 Article en page(s) : pp. 7403-7413 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Controllability Résumé : Chemical processes usually involve several alternative manipulated variables each having the potential to influence system operability. This work presents a methodology that illustrates how manipulated variables selection can relate to the open-loop stability and phase behavior of chemical processes over the entire feasible operating region. Within this framework, the first step explores the steady state maps, under different manipulated variable selections. The inherent characteristics, including open-loop stability and phase behavior, are then analyzed. After that, the effect of manipulated variable selection on the static controllability can be assessed. In the third step, based on the conventional model predictive controller, closed-loop dynamic simulations, with both reference tracking and disturbance rejection, are carried out. This allows the comparison of dynamic behaviors, under different operating policies, and a validation of outcomes from the open-loop theoretical analysis. Results from both the static and the dynamic analysis reveal the influence of the manipulated variable selection on the process controllability, over the feasible operating region. These conclusions can assist in process control structure selection and process operation. The proposed method is applied to a polymerization reaction process to demonstrate its efficiency. This example emphasizes how such a methodology can help clarify and handle the causes of the complex phenomena that arise in the design, operation, and control of chemical processes. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24239056 [article] Effect of manipulated variables selection on the controllability of chemical processes [texte imprimé] / Zhihong Yuan, Auteur ; Bingzhen Chen, Auteur ; Jinsong Zhao, Auteur . - 2011 . - pp. 7403-7413. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 12 (Juin 2011) . - pp. 7403-7413 Mots-clés : Controllability Résumé : Chemical processes usually involve several alternative manipulated variables each having the potential to influence system operability. This work presents a methodology that illustrates how manipulated variables selection can relate to the open-loop stability and phase behavior of chemical processes over the entire feasible operating region. Within this framework, the first step explores the steady state maps, under different manipulated variable selections. The inherent characteristics, including open-loop stability and phase behavior, are then analyzed. After that, the effect of manipulated variable selection on the static controllability can be assessed. In the third step, based on the conventional model predictive controller, closed-loop dynamic simulations, with both reference tracking and disturbance rejection, are carried out. This allows the comparison of dynamic behaviors, under different operating policies, and a validation of outcomes from the open-loop theoretical analysis. Results from both the static and the dynamic analysis reveal the influence of the manipulated variable selection on the process controllability, over the feasible operating region. These conclusions can assist in process control structure selection and process operation. The proposed method is applied to a polymerization reaction process to demonstrate its efficiency. This example emphasizes how such a methodology can help clarify and handle the causes of the complex phenomena that arise in the design, operation, and control of chemical processes. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24239056

Fault diagnosis of batch chemical processes using a dynamic time warping (DTW)-based Artificial Immune System / Yiyang Dai in Industrial & engineering chemistry research, Vol. 50 N° 8 (Avril 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 8 (Avril 2011) . - pp. 4534–4544 Titre : Fault diagnosis of batch chemical processes using a dynamic time warping (DTW)-based Artificial Immune System Type de document : texte imprimé Auteurs : Yiyang Dai, Auteur ; Jinsong Zhao, Auteur Année de publication : 2011 Article en page(s) : pp. 4534–4544 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Chemical  processes Résumé : Fault diagnosis is important for ensuring chemical processes stability and safety. The strong nonlinearity and complexity of batch chemical processes make such diagnosis more difficult than that for continuous processes. In this paper, a new fault diagnosis methodology is proposed for batch chemical processes, based on an artificial immune system (AIS) and dynamic time warping (DTW) algorithm. The system generates diverse antibodies using known normal and fault samples and calculates the difference between the test data and the antibodies by the DTW algorithm. If the difference for an antibody is lower than a threshold, then the test data are deemed to be of the same type of this antibody’s fault. Its application to a simulated penicillin fermentation process demonstrates that the proposed AIS can meet the requirements for online dynamic fault diagnosis of batch processes and can diagnose new faults through self-learning. Compared with dynamic locus analysis and artificial neural networks, the proposed method has better capability in fault diagnosis of batch processes, especially when the number of historical fault samples is limited. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101465b [article] Fault diagnosis of batch chemical processes using a dynamic time warping (DTW)-based Artificial Immune System [texte imprimé] / Yiyang Dai, Auteur ; Jinsong Zhao, Auteur . - 2011 . - pp. 4534–4544. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 8 (Avril 2011) . - pp. 4534–4544 Mots-clés : Chemical  processes Résumé : Fault diagnosis is important for ensuring chemical processes stability and safety. The strong nonlinearity and complexity of batch chemical processes make such diagnosis more difficult than that for continuous processes. In this paper, a new fault diagnosis methodology is proposed for batch chemical processes, based on an artificial immune system (AIS) and dynamic time warping (DTW) algorithm. The system generates diverse antibodies using known normal and fault samples and calculates the difference between the test data and the antibodies by the DTW algorithm. If the difference for an antibody is lower than a threshold, then the test data are deemed to be of the same type of this antibody’s fault. Its application to a simulated penicillin fermentation process demonstrates that the proposed AIS can meet the requirements for online dynamic fault diagnosis of batch processes and can diagnose new faults through self-learning. Compared with dynamic locus analysis and artificial neural networks, the proposed method has better capability in fault diagnosis of batch processes, especially when the number of historical fault samples is limited. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie101465b