Abstract

This short communication presents a methodology to detect abnormal gas dispersion conditions in flotation machines. These abnormal conditions are characterized by the significant presence of cap-shaped bubbles. The approach considers the use of a bubble size analyzer to measure gas dispersion at industrial scale. The detection of abnormal conditions is critical when estimating bubble size by automated software. Otherwise, the estimates are significantly biased, since irregular bubbles are typically removed from the analysis. From the recorded images and the respective black and white representation, the variability of the shadow percentage caused by the bubbles in the vision field, abruptly increases in the presence of cap-shaped bubbles. Experimental conditions with coefficients of variation lower than 60-70% in the shadow percentage represent spherical and spherical-ellipsoidal regimes. In the former, automated bubble sizing software has proved to be sufficiently effective in obtaining reliable results. In the latter, different segmentation techniques have been proposed to obtain satisfactory results. Abnormal conditions are detected under coefficients of variation greater than 80% in the shadow percentage. The presence of cap-shaped bubbles causes inefficiencies in the collection of hydrophobic minerals in the pulp zone as well as disturbances in the separation stage (froth zone). Therefore, the detection of these irregular bubbles is suitable to provide feedback to flotation processes, allowing gas dispersion to be driven towards normal operating conditions.