Application of Data Mining Methods in Eluxyl Process

Author

Ren, Jia ; Ma, Chaoyang ; Su, Hongye ; Chu, Jian

Author_Institution

Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou

Volume

2

fYear

0

fDate

0-0 0

Firstpage

7697

Lastpage

7701

Abstract

Eluxyl process is a simulated moving bed process. It achieves PX (paraxylene) separation from its other aromatic isomers. One year´s historical data of Eluxyl process were studied, and data mining methods were introduced to extract useful operation information from them. Three main data mining procedures were discussed. Data preprocessing was discussed first. Then PCA (principal components analysis) and K-means clustering technology were introduced and applied to discover different operational conditions in different loads. Finally fuzzy classification based on associations (FCBA) algorithm was used to discover the main reasons that lead to performance fluctuations and the rules denoting the typical operations

Keywords

chemical technology; data mining; fuzzy set theory; manufacturing processes; pattern classification; pattern clustering; principal component analysis; Eluxyl process; K-means clustering technology; aromatic isomers; data mining; data preprocessing; fuzzy classification based on association algorithm; information extraction; paraxylene separation; principal component analysis; simulated moving bed process; Chaos; Clustering algorithms; Data mining; Data preprocessing; Feeds; Fluctuations; Industrial control; Laboratories; Principal component analysis; Process control; Data Mining; Eluxyl process; Fuzzy classification based on associations (FCBA);

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713465

Filename

1713465