A new novel data reconciliation model

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.