Research On Application Of Data Reconciliation

In petrochemical production processes, the input and output variables of production device and any other parameters have very important significance. In process of actual production, measurement error is often present, therefore data reconciliation is useful. However, due to the complexity of the process, it is difficult to get the reliable input and output data. Through the application of data reconciliation, we can eliminate or reduce the impact of the measurement error on process, and also can improve the accuracy and balance of the data. Based on the development of steady-state data reconciliation and dynamic data reconciliation, this paper proposes CVA dynamic data reconciliation method. Research and simulation results show that CVA dynamic data reconciliation can make better results. This paper mainly discusses the following points:1. Literature on data reconciliation, gross error detection and sensor network redundancy analysis is surveyed. Advances in the theory and application of data rectification are reviewed.2. The principles of sensor network redundancy analysis, gross error detection and data reconciliation in linear systems are introduced.3. The technical development of dynamic data reconciliation is elaborated. Furthermore, the article raises CVA dynamic data reconciliation method.4. TE process is a representative model of a kind of chemical production processes, thus the paper uses TE process as an application example for the data reconciliation. The simulation results show that CVA dynamic data reconciliation method can effectively coordinate the data. And this method can be appropriately applied to the actual process of industrial production.5. Finally this paper also summarizes the research, and prospects the application of CVA dynamic data reconciliation.