DocumentCode :
1563087
Title :
Research on the application of data-mining for quality analysis in petroleum refining industry
Author :
Chen, Jiang ; Fan, Quanyi ; Xu, Bowen
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume :
5
fYear :
2004
Firstpage :
4314
Abstract :
High product quality is the main target of the petroleum refining industry. It is widely admitted that there are some limitations of traditional product-quality-monitoring methods. Data-mining (DM) is a method to get useful information, which other regular methods cannot find, from enormous data. Data warehouse (DW) is the best way to store and manage massive enterprise data and provide a strong support to data analysis methods. This paper presents a new framework to deal with quality analysis, which combines the soft sensor, DM and DW. It promises to overcome the limitations of soft sensor and apply soft sensor in quality analysis in the petroleum refining industry.
Keywords :
data analysis; data mining; data warehouses; monitoring; oil refining; petroleum industry; production engineering computing; quality control; data analysis; data mining; data warehouse; petroleum refining industry; product quality monitoring methods; quality analysis; soft sensor; Automation; Data analysis; Data mining; Data warehouses; Delta modulation; Fuel processing industries; Instruments; Petroleum industry; Refining; Sensor phenomena and characterization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1342326
Filename :
1342326
Link To Document :
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