Reconciliation of mineral processing data containing correlated measurement errors

Steady-state values of stream properties (species flowrates) of a mineral processing circuit are usually estimated by averaging values sampled during a given time interval. A major source of data inaccuracy is the integration error, i.e. the error generated by the dynamic variations of the stream properties around their steady-state values. The paper shows that these sampling errors are significantly reduced by appropriate reconciliation methods based on material conservation equations. The optimal error compensation is obtained by minimizing a quadratic function where the weighting factors take into account the integration error covariance from stream to stream and species to species. The method is illustrated for a flotation circuit modelled by a state-space representation. The data variance reduction is compared for different weighting strategies of a quadratic reconciliation criterion. For the studied system, it seems that ignoring measurement error correlation, using a standard weighted least-squares criterion instead of the optimal quadratic function, does not degrade too much the ability of the reconciliation procedure to reduce the data variance. (C) 1998 Elsevier Science B.V. All rights reserved.