Mass Balance Reconciliation for Bilinear Systems: A Case Study of a Raw Mill Separator in a Typical Moroccan Cement Plant

  • S. Fellaou Laboratory for Analysis and Synthesis of Industrial Processes (LASPI), University Mohammed V Agdal Rabat, Mohammadia School of Engineers, Rabat, Morocco
  • T. Bounahmidi Laboratory for Analysis and Synthesis of Industrial Processes (LASPI), University Mohammed V Agdal Rabat, Mohammadia School of Engineers, Rabat, Morocco and Euro-Mediterranean University of Fez (UEMF), Fez, Morocco
Keywords: mass balance, data reconciliation, bilinear system, cement industry


Stream flow rates and their several compositions are measured in a typical cement raw mill separator. In order to simultaneously reconcile flow and composition measurements in this circuit, the component mass balances was included as constraints which contain the products of flow rate and composition variables in the data reconciliation problem. In this paper, the effectiveness of simultaneous procedures for bilinear data reconciliation is established, the numerical problem constraints were coded in MATLAB and a mass balance model is built. Moreover, based on the difference between the measured and reconciled data it was found that it performs optimally.


Download data is not yet available.


A. Spindler, “Structural redundancy of data from wastewater treatment systems. Determination of individual balance equations”, Water Res., Vol. 57, pp. 193–201, 2014

C. Karlsson, Tools for reconciliation of measurement data for processes at steady-state, Mälardalen University, 2004

H. Davidson, D. R. Kuehn, “Computer control II: mathematics of control”, Chem. Eng. Prog., Vol. 57, No. 6, pp. 1653-1672, 1961

V. Václavek, Studies on System Engineering. III: Optimal Choice of the Balance Measurements in Complicated Chemical Systems, Chemical Engineering Science, Vol. 24, No. 6, pp. 947-955, 1969

R. S. H. Mah, Chemical process structures and information flows, Elsevier, 1990

H. S. Yi, H. Shin, J. H. Kim, C. Han, “Industrial application of gross error estimation and data reconciliation to by production gases in iron and steel making plants”, in International Conference on Control, Automation and Systems, Muju Resort, Jeonbuk, Korea, 2001

M. J. Bagajewicz, E. Cabrera, “Data Reconciliation in Gas Pipeline Systems”, Ind. Eng. Chem. Res., Vol. 42, No. 22, pp. 5596–5606, 2003

D. Özyurt, R. Pike, “Theory and practice of simultaneous data reconciliation and gross error detection for chemical processes”, Comput. Chem. Eng., Vol. 28, pp. 381–402, 2004

M . Schladt, B . Hu, “Soft-sensors Based on Nonlinear Steady-State Data Reconciliation in the Process Industry”, Chem. Eng. Process., Vol. 46, No. 11, pp. 1107–1115, 2007

M. F. Martins, C. Amaro, L. S. Souza, R. Kalid, A. Kiperstok, “New objective function for data reconciliation in water balance from industrial processes”, J. Clean. Prod., Vol. 18, No. 12, pp. 1184–1189, 2010

X. Jiang, P. Liu, Z. Li, “A Data Reconciliation Based Approach to Accuracy,” Vol. 35, No. 2003, pp. 1213–1218, 2013.

A. E. Morris, G. Geiger, H. Alan, Handbook on material and energy balance calculations in materials processing third edition, NJ, USA: John Wiley & Sons, Inc, 2011

C. Maurice. Fuerstenau and N. Kenneth and Han, Principles of Mineral Processing. USA, 2009

M. Langenstein, J. Jansky, “Process data reconciliation in nuclear power plants”, Process data, Vol. 2, pp. 1–9, 2003

J. Ragot, M. Aubrun, M. Darrouach, “Equilibrage de Bilan matière méthodes et exemples minéralurgiques”, Control Comput., Vol. 11, pp. 50–59, 1983

J. Romagnoli, M. C. Sánchez, Data processing and reconciliation for chemical process operations, Academic Press, San Diego, 2000



Abstract Views: 329
PDF Downloads: 134

Metrics Information
Bookmark and Share