DocumentCode :
643053
Title :
Successive difference method for steady state detection in univariate system
Author :
Gootam, Manoj K. ; Kubal, Nandkishor ; Nallasivam, Ulaganathan
Author_Institution :
Chem. Eng. Dept., Indian Inst. of Technol., Madras, Chennai, India
fYear :
2013
fDate :
28-30 Aug. 2013
Firstpage :
912
Lastpage :
916
Abstract :
The use of online data for steady-state detection is required to solve problems like statistical data reconciliation, real time optimization and controller performance monitoring. In this paper, a new method for univariate system is proposed, which makes use of successive differences of time series (single variate) data. The method is simple because the parameters on which it is based are easy to tune as they are rather intuitive. Also this method needs less computation time as it does not involve any model fitting exercise as the case with other methods like polynomial interpolation technique. In order to assess the performance of the above method, a comparison analysis based on its performance in accurately detecting the steady state part that is present in a set of industrial time series data was performed. The performance of this method is compared with the three best existing methods that are available in the current literature. This analysis showed that the proposed method, Successive Difference method is most robust and its performance is better than the existing three methods.
Keywords :
time series; computation time; industrial time series data; online data; single-variate data; steady-state detection; successive difference method; univariate system; Data models; Noise; Optimization; Polynomials; Standards; Steady-state; Time series analysis; steady-state; time series; univariate system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Applications (CCA), 2013 IEEE International Conference on
Conference_Location :
Hyderabad
ISSN :
1085-1992
Type :
conf
DOI :
10.1109/CCA.2013.6662867
Filename :
6662867
Link To Document :
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