Data Acquisition from an Industrial Zinc Flotation Circuit

"The data acquisition from industrial plants is a fundamental step for process modelling in process optimization, process analysis and automatic control.The introduction, some years ago, of modern distributed control and data acquisition systems in concentrators imposes a new approach in designing experimental schemes for data acquisition campaigns and new criteria for the treatment of the obtained discrete information.This paper presents the methodology applied to sample a zinc flotation circuit at Les Mines Selbaie, Joutel, PQ. Values of 85 process variables were obtained form the Distributed Control and Data Acquisition System (Bailey Network 90) and transferred to the DOS environment. Another 11 variables (flowrates and valve positions) were directly sampled using an IBM-PC compatible computer equipped with a data acquisition card and a signal processing circuit.All variables, under the vector form, were processed in the PC-MATLAB environment to either filter or eliminate the non-linear disturbances and noises, producing useful data for model development. The filtering algorithms are also presented.INTRODUCTIONProcess control does not need to be justified. Whether manual or automatic, any processing plant requires some form of control to accomplish its main objectives: a good quality product and a target throughput. Process control of mineral processing plants has steadily evolved from manual control, where the operator skills and/or experience play an important role, to some level of automatic control, usually considered better, as less human subjectivity is involved, at least when actions have to be taken.The design of these control systems requires the knowledge of the dynamics of the process it is deemed to control. Process modelling is therefore an essential step in the assessment and the design of a control strategy. The choice of model will depend on the available resources and manpower."