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.

本研究调查了通过在 Magotteaux 球磨机上进行声学测量来预测矿石可磨性特征和变化的矿浆密度的倾向。具体而言，两种不同磨机进料（模型石英和铁矿石）的研磨行为以及固体负载（50、57 和 67 wt% 固体）与测量的声学信号相关。均方根 (RMS) 和功率谱密度技术的声学响应分析表明，模型石英样品在研磨过程中比铁矿石样品发出更高的能量，这与它们不同的硬度特性有关。RMS 分析还表明，两个样品的噪声强度随着研磨时间的增加而显着降低，这与它们的研磨校准曲线非常吻合。选定的纸浆密度在声发射方面显示出微小的差异，这反映在它们的产品尺寸分布上。这项研究的结果进一步显示了使用声学传感器作为实时磨机进料特性、磨机运行监控和优化的代理的潜力。