DocumentCode
2083068
Title
A MT-NT-MILP combined method for gross error detection and data reconciliation
Author
Sun, Shaochao ; Dao, Huang ; Gong, Yanxue
Author_Institution
School of Information Science and Engineering; East China University of Science and Technology Shanghai 20037, China
fYear
2010
fDate
4-6 Dec. 2010
Firstpage
3439
Lastpage
3442
Abstract
Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. In this paper, a MT-NT-MILP (MNM)combined method is developed for gross error detection and data reconciliation for industrial application. An improved MT-NT method is proposed in order to generate gross error candidates before data rectification. Candidates are used in the MILP objective function to improve the efficiency by reducing the number of binary variables. Simulation results show that the method is effective especially in a large-scale problem.
Keywords
Chemical engineering; Equations; Graphics; Materials; Mathematical model; Measurement uncertainty; Robustness; MILP; MT; NT; data rectification; graphic theory; gross error detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location
Hangzhou, China
Print_ISBN
978-1-4244-7616-9
Type
conf
DOI
10.1109/ICISE.2010.5688570
Filename
5688570
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