Predicting mill feed grind characteristics through acoustic measurements

The present study investigates the propensity of predicting ore grindability characteristics and varying pulp densities through acoustic measurements on the Magotteaux ball mill. Specifically, the grinding behaviour of two different mill feeds (model quartz and iron ore) together with solid loadings (50, 57, and 67 wt% solids) were correlated against measured acoustic signals. The acoustic response analysis by root mean square (RMS) and power spectral density techniques indicated that model quartz sample emits higher energies than iron ore sample during grinding, relating to their different hardness properties. RMS analysis also showed that the noise intensities of both samples depreciate considerably as a function of increasing grind time, which corresponds well with their grind calibration curves. The selected pulp densities showed marginal differences in acoustic emission, which was reflected in their product size distribution. Results from this study further show the potential of using acoustic sensors as a proxy for real-time mill feed characteristics, mill operation monitoring and optimisation.

Automated summary

The present study investigates the prediction of ore grindability characteristics and varying pulp densities through acoustic measurements on the Magotteaux ball mill. It was found that the model quartz sample emits higher energies than the iron ore sample during grinding, correlating with their different hardness properties. The noise intensities of both samples decrease significantly with increasing grind time, and there are marginal differences in acoustic emission among the selected pulp densities.