Documents disponibles écrits par cet auteur

Development of soft sensor models based on time difference of process variables with accounting for nonlinear relationship / Hiromasa Kaneko in Industrial & engineering chemistry research, Vol. 50 N° 18 (Septembre 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 18 (Septembre 2011) . - pp. 10643–10651 Titre : Development of soft sensor models based on time difference of process variables with accounting for nonlinear relationship Type de document : texte imprimé Auteurs : Hiromasa Kaneko, Auteur ; Kimito Funatsu, Auteur Année de publication : 2011 Article en page(s) : pp. 10643–10651 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Process  variables Résumé : Soft sensors are widely used to estimate process variables that are difficult to measure online. Though regression models are reconstructed with new data to adapt changes of the plants, some problems remain in practice. Hence, it is attempted to construct soft sensor models based on the time difference of an objective variable and that of explanatory variables for reducing the effects of deterioration with age such as the drift and gradual changes in the state of plants. In this paper, we have proposed to construct time difference models after modeling nonlinear relationship between and among process variables. Variables obtained by physical models or those calculated by statistical nonlinear regression methods are used to consider the nonlinearity, and then, a time difference model is constructed including these variables. We applied these methods to the actual industrial data obtained during an industrial polymer process and confirmed the usefulness of the proposed methods. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie200692m [article] Development of soft sensor models based on time difference of process variables with accounting for nonlinear relationship [texte imprimé] / Hiromasa Kaneko, Auteur ; Kimito Funatsu, Auteur . - 2011 . - pp. 10643–10651. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 18 (Septembre 2011) . - pp. 10643–10651 Mots-clés : Process  variables Résumé : Soft sensors are widely used to estimate process variables that are difficult to measure online. Though regression models are reconstructed with new data to adapt changes of the plants, some problems remain in practice. Hence, it is attempted to construct soft sensor models based on the time difference of an objective variable and that of explanatory variables for reducing the effects of deterioration with age such as the drift and gradual changes in the state of plants. In this paper, we have proposed to construct time difference models after modeling nonlinear relationship between and among process variables. Variables obtained by physical models or those calculated by statistical nonlinear regression methods are used to consider the nonlinearity, and then, a time difference model is constructed including these variables. We applied these methods to the actual industrial data obtained during an industrial polymer process and confirmed the usefulness of the proposed methods. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie200692m

Statistical approach to constructing predictive models for thermal resistance based on operating conditions / Hiromasa Kaneko in Industrial & engineering chemistry research, Vol. 51 N° 29 (Juillet 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9906-9912 Titre : Statistical approach to constructing predictive models for thermal resistance based on operating conditions Type de document : texte imprimé Auteurs : Hiromasa Kaneko, Auteur ; Susumu Inasawa, Auteur ; Nagisa Morimoto, Auteur Année de publication : 2012 Article en page(s) : pp. 9906-9912 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Operating  conditions  Forecast  model Résumé : We have constructed statistical models that predict thermal resistance after fouling layer formation in a heat exchanger, in which a slurry of stearic acid in toluene was cooled. Chemoinformatics was used, and the initial rate of increase in thermal resistance (dU―1/dt) was calculated from experimental conditions such as coolant flow rate and the degree of supersaturation. We then constructed models for thermal resistance at a steady state using calculated values of dU―1/dt and experimental conditions. Our model gives a good correlation with the experimental results. The contribution of operating conditions to fouling layer formation was discussed semiquantitatively on the basis of linear regression coefficients that were obtained from our model. Because only operating conditions and set values were used as input, our approach is very practical for prediction of thermal resistance given certain operating conditions. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184969 [article] Statistical approach to constructing predictive models for thermal resistance based on operating conditions [texte imprimé] / Hiromasa Kaneko, Auteur ; Susumu Inasawa, Auteur ; Nagisa Morimoto, Auteur . - 2012 . - pp. 9906-9912. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9906-9912 Mots-clés : Operating  conditions  Forecast  model Résumé : We have constructed statistical models that predict thermal resistance after fouling layer formation in a heat exchanger, in which a slurry of stearic acid in toluene was cooled. Chemoinformatics was used, and the initial rate of increase in thermal resistance (dU―1/dt) was calculated from experimental conditions such as coolant flow rate and the degree of supersaturation. We then constructed models for thermal resistance at a steady state using calculated values of dU―1/dt and experimental conditions. Our model gives a good correlation with the experimental results. The contribution of operating conditions to fouling layer formation was discussed semiquantitatively on the basis of linear regression coefficients that were obtained from our model. Because only operating conditions and set values were used as input, our approach is very practical for prediction of thermal resistance given certain operating conditions. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184969

Visualization of models predicting transmembrane pressure jump for membrane bioreactor / Hiromasa Kaneko in Industrial & engineering chemistry research, Vol. 51 N° 28 (Juillet 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 28 (Juillet 2012) . - pp. 9679-9686 Titre : Visualization of models predicting transmembrane pressure jump for membrane bioreactor Type de document : texte imprimé Auteurs : Hiromasa Kaneko, Auteur ; Kimito Funatsu, Auteur Année de publication : 2012 Article en page(s) : pp. 9679-9686 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Bioreactor  Membrane  reactor  Prediction  Modeling Résumé : Membrane bioreactors (MBRs) have been widely used to purify wastewater for reuse. However, MBRs are subject to fouling, which is the phenomenon whereby foulants absorb or deposit on the membrane. After the operation of MBRs in the long term under constant-rate filtration, transmembrane pressure (TMP) increases rapidly. We previously proposed a model predicting the time of this TMP jump, but it is difficult to investigate optimal operating conditions and parameters where TMP jumps can be prevented from occurring. In this paper, we have proposed to visualize the domains where the discriminant model estimates TMP jumps will happen by using visualization methods. In prediction, new data are projected to the map, and accordingly, we can discuss the possibility of TMP jumps and optimal MBR conditions in the future. The performance of the proposed method was confirmed through the analyses of two data sets obtained from other papers. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26163305 [article] Visualization of models predicting transmembrane pressure jump for membrane bioreactor [texte imprimé] / Hiromasa Kaneko, Auteur ; Kimito Funatsu, Auteur . - 2012 . - pp. 9679-9686. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 28 (Juillet 2012) . - pp. 9679-9686 Mots-clés : Bioreactor  Membrane  reactor  Prediction  Modeling Résumé : Membrane bioreactors (MBRs) have been widely used to purify wastewater for reuse. However, MBRs are subject to fouling, which is the phenomenon whereby foulants absorb or deposit on the membrane. After the operation of MBRs in the long term under constant-rate filtration, transmembrane pressure (TMP) increases rapidly. We previously proposed a model predicting the time of this TMP jump, but it is difficult to investigate optimal operating conditions and parameters where TMP jumps can be prevented from occurring. In this paper, we have proposed to visualize the domains where the discriminant model estimates TMP jumps will happen by using visualization methods. In prediction, new data are projected to the map, and accordingly, we can discuss the possibility of TMP jumps and optimal MBR conditions in the future. The performance of the proposed method was confirmed through the analyses of two data sets obtained from other papers. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26163305