H. Hyötyniemi and J. Miettunen (Finland)
Data reconciliation, sensor fusion, subspace identification, independent components; dynamic models, filtering, state estimation, Kalman filter; X-ray analysis, flotation process.
Data reconciliation is a technique to enhance measurement data by exploiting the a priori structure of the process plant. However, in many cases this structure is not exactly known. In this paper, possibilities for exploiting the multivariate statistical methods are studied for constructing a dynamic data reconciliation scheme applying subspace identification and Kalman filtering. As an application example, X-ray analyzer operating in a zinc flotation circuit is studied.
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