The Modified SICC Algorithm in Gross Error Detection

Jun. 2005

Turn off MathJax

Article Contents

Abstract

References

INFORMATION AND CONTROL > 2005 > 34(3): 291-295.

ZHOU Ling-ke, SU Hong-ye, CHU Jian. The Modified SICC Algorithm in Gross Error Detection[J]. INFORMATION AND CONTROL, 2005, 34(3): 291-295.

Citation:

ZHOU Ling-ke, SU Hong-ye, CHU Jian. The Modified SICC Algorithm in Gross Error Detection[J]. INFORMATION AND CONTROL, 2005, 34(3): 291-295.

Citation:

ZHOU Ling-ke, SU Hong-ye, CHU Jian. The Modified SICC Algorithm in Gross Error Detection[J]. INFORMATION AND CONTROL, 2005, 34(3): 291-295.

1.
Department of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
2.
Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China

Abstract

A modified SICC (serial identification with collective compensation) method used in gross error detection and data reconciliation for chemical process is introduced in this paper. By using temporal redundancy, upper and lower bounds of process measurements are added in the modified SICC method to avoid the misidentification of gross errors. To prevent the computation of project matrix, the measurements are compensated by using the estimated gross error magnitudes after each gross error is identified, and after that, MT (measu rement test) method is used to find the gross error candidates. To avoid the singularities from appearing after gross error compensation, necessary cycle detection is added. Simulation results on a steam metering system verify the effective ness of the modified algorithm.
- data reconciliation,
- gross error detection

FullText(HTML)

[1]	Mah R S H, Tamhane A C. Detection of gross errors in process data [J]. American Institute of Chemical Engineering, 1982,28(5):828～830.
[2]	Mah R S H, Stanley G M, et al. Reconciliation and rectification of process flow and inventory data [J]. Industrial and Engineering Chemistry Process Design and Development, 1976, 15(1):175～183.
[3]	Bagajewicz M, Jiang Q Y. Gross error modeling and detection in plant linear dynamic reconciliation [J]. Computers and Chemical Engineering, 1998,22 (12): 1789～1809.
[4]	Sanchez M, Romagnoli J, et al. Simultaneous estimations of biases and leaks in process plants [J]. Computers and Chemical Engineering, 1999,23 (7):841～858.
[5]	Jiang Q Y, Bagajewicz M. On a strategy of serial identification with collective compensation for multiple gross error estimation in linear steady-state reconciliation [J]. Industrial Engineering of Chemical Research, 1999,38 (5):2119～2128.
[6]	Serth R W, Heehan W A. Gross error detection and data reconciliation in steam-metering systems [J]. American Institute of Chemical Engineering, 1986, 32(5):733～742.
[7]	Crowe C M, Hrymak A, Garcia Campos Y A. Reconciliation of process flow rates by matrix projection- I: linear case [J]. American Institute of Chemical Engineering, 1983,29 (5): 881～895.
[8]	袁永根,李华生.过程系统测量数据校正技术[M].北京:中国石化出版社,1996.