INTEGRATED OPERATION SUPPORT SYSTEM (IOpSS) THE DATA PRE-PROCESSING AND DATA RECONCILIATION MODULES

This paper discusses the current developments within a novel environment to perform related model-based activities. In particular, the paper focuses in the modules corresponding to data preprocessing and dynamic data reconciliation. In terms of the former module, this work discusses the implementation of three approaches based on the minimum median distance (MMD), the moving median (MM), and the modified MT filter for the detection of outliers. Regarding the data reconciliation module, the error-in-variable method (EVM) was implemented in gPROMS as an important extension to the environment. Finally, the pre-processed data was used to evaluate the performance of the different outlier detection/cleaning methods in the dynamic EVM data reconciliation. Results show that the MM filter has the best performance among the outlier cleaning techniques, followed by the modified MMD method. It is demonstrated that the current EVM implementation is able to perform the reconciliation for complex non-linear dynamic modules and at the same time to estimate parameters and gross errors.