Fault detection based on acoustic emission-early agglomeration recognition system in fluidized bed reactor / Yefeng Zhou in Industrial & engineering chemistry research, Vol. 50 N° 14 (Juillet 2011)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 50 N° 14 (Juillet 2011) . - pp. 8476-8484 Titre : Fault detection based on acoustic emission-early agglomeration recognition system in fluidized bed reactor Type de document : texte imprimé Auteurs : Yefeng Zhou, Auteur ; Kezeng Dong, Auteur ; Huang Zhengliang, Auteur Année de publication : 2011 Article en page(s) : pp. 8476-8484 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Fluidized bed reactor Agglomeration Acoustic emission Failure detection Résumé : Agglomeration is one of the most challenging problems due to overheating of the particles in fluidized bed reactors (FBRs). Therefore, it is an urgent task to develop a reliable and sensitive method, which can help accurately detect the agglomeration in an early stage. In this study, acoustic emission-early agglomeration recognition system (AE-EARS) has been put forward for fault detection. Based on acoustic emission signals, the attractor comparison method was developed for prewarning the agglomeration in lab-scale and pilot-scale apparatus. The results concluded from this study demonstrated that the statistical characteristic S acts more sensitively to small agglomeration when compared with the malfunction coefficients CD2 and CK2, and other traditional measurement techniques (such as γ ray, temperature, and pressure difference). Besides, model optimization based on AE-EARS can help to select the criterion and improve the rate of false alarm. The analysis methods based on AE-EARS can warn the agglomeration earlier, faster, and more accurately. Especially the S value based on the attractor comparison, can be used as an indicator for "early recognition", which enjoys a broad prospect in industrial application. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24346887 [article] Fault detection based on acoustic emission-early agglomeration recognition system in fluidized bed reactor [texte imprimé] / Yefeng Zhou, Auteur ; Kezeng Dong, Auteur ; Huang Zhengliang, Auteur . - 2011 . - pp. 8476-8484. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 14 (Juillet 2011) . - pp. 8476-8484 Mots-clés : Fluidized bed reactor Agglomeration Acoustic emission Failure detection Résumé : Agglomeration is one of the most challenging problems due to overheating of the particles in fluidized bed reactors (FBRs). Therefore, it is an urgent task to develop a reliable and sensitive method, which can help accurately detect the agglomeration in an early stage. In this study, acoustic emission-early agglomeration recognition system (AE-EARS) has been put forward for fault detection. Based on acoustic emission signals, the attractor comparison method was developed for prewarning the agglomeration in lab-scale and pilot-scale apparatus. The results concluded from this study demonstrated that the statistical characteristic S acts more sensitively to small agglomeration when compared with the malfunction coefficients CD2 and CK2, and other traditional measurement techniques (such as γ ray, temperature, and pressure difference). Besides, model optimization based on AE-EARS can help to select the criterion and improve the rate of false alarm. The analysis methods based on AE-EARS can warn the agglomeration earlier, faster, and more accurately. Especially the S value based on the attractor comparison, can be used as an indicator for "early recognition", which enjoys a broad prospect in industrial application. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24346887

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