Detection of systematic errors in the data used for mass balancing using the Movazen© software, M.R. Yarahmadi, S.R. Mortazavi, and S. Banisi

Nowadays the development of automatic on-line sampling systems has enabled large amounts of data to be available to plant managers. These data are inevitably prone to random and sometimes systematic errors. Data reconciliation methods are used to deal with random errors. In these methods, the measured data are adjusted in accordance to their error, so that the mass conservation law is satisfied at the same time. Measured data may also contain systematic errors, using these data in mass balancing software will result in inaccurate or even irrational results. In this paper three methods for detecting systematic errors (global test, node constraint test and maximum power constraint test) were presented. A step by step method to locate the systematic errors was demonstrated. Then, the new version of Movazen©, a mass balancing software, was introduced and used to locate systematic errors in the measurements taken from the Sarcheshmeh pilot plant copper flotation circuit. Keywords: Mass balancing, data reconciliation, random error, systematic error