在选矿科研和实际生产中,经常采取—2毫米原矿进行筛分分析,以观察目的金属在各粒级中的分布情况。但是,对这些测试数据的利用,多限于宏观上的评估,而用于规律性的分析较少。本文作皆提出的方法是,利用较粗的原矿筛析数据,进行ε-γ图象分析,借助矿物的特征富集峰,预测矿物浮选的磨矿(包括粗磨及再磨)粒度和磨矿 In ore dressing scientific research and actual production, it is common to take 2 mm ore for sieving analysis to observe the distribution of the target metal in each grain size. However, the use of these test data is mostly limited to the macroscopic assessment, and less regular analysis. The method proposed in this paper is to use the raw ore to sieve the data and carry out the ε-γ image analysis. The mineralogical features are used to enrich the peak to predict the particle size of the mineral flotation (including coarse grinding and reground grinding) and Grinding