Title :
A new novel data reconciliation model
Author :
Weijian, Cai ; Xiao, Qu
Author_Institution :
Coll. of Autom. & Electr. Eng., Zhe Jiang Univ. of Sci. & Technol., Hang Zhou, China
Abstract :
Traditional data reconciliation model tends to spread the gross errors overall the measurements, in order to avoid the problem this paper proposed a new data reconciliation model In this work, some new constraints derived from the ratio of measurements is inducted and the constraint conditions based on material balance are put into soft constraints form by using the method of penalty function The data reconciliation procedure using the improved model tends to make the measurements having gross errors get more effect than the others. Thereby, the new data reconciliation model is more robust than the old. Based on the results of the new model, the measurement test method can be used to detect gross errors, and the result of simulations shows that the gross error detection base the new data reconciliation model is very sensitive to presence of gross errors and has a great probability of correctly finding one or several gross errors.
Keywords :
constraint handling; data handling; constraint conditions; data reconciliation model; gross errors; material balance; soft constraints; Chemical processes; Data models; Electrical engineering; Materials; Mathematics; Measurement uncertainty; Robustness; constraint conditions; data reconciliation; detection; gross error; penalty function;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5777253