基于旋转分类模糊纹理谱的矿物浮选泡沫平滑度分析(英文)

Froth homogeneity analysis using rotate classification fuzzy texture spectrum for mineral flotation process monitoring

矿物浮选的精矿品位与泡沫的纹理复杂度密切相关.为了避免纹理谱方法中像素值的刚性比较,提出了一种新的基于旋转分类模糊纹理谱的纹理描述方法用于金属矿物分离.经过指数函数拟合频率分布曲线,确定模糊阈值大小,统计模糊纹理单元,给出了灰度差值的模糊纹理谱,并利用旋转分类将6561种纹理单元简化至834种.基于此,引入2个描述因子,纹理平滑度与粗糙度.实际应用结果表明,纹理平滑度可描述图像纹理粗糙程度,同时反映实时矿物品位.

The concentration grade in mineral flotation is closely related to the froth texture complexity. To deal with the defects of rigid comparison of basic texture spectrum, we present a novel rotate classification fuzzy texture spectrum method for mineral separation process from engineering aspects. The frequency-statistics curve of neighborhood pixels grayscale difference is fitted by using an exponential function, and the optimal threshold value of the fuzzy internal is determined. According to the grayscale difference between neighborhood pixels and seed pixel in local region, the fuzzy texture unit is constructed, which is used to calculate the fuzzy texture spectrum of various fuzzy texture unit numbers. Meanwhile, the original 6561 texture units are simplified to 834 classes. The homogeneity and the coarseness are introduced to describe the froth texture feature. The analysis results of froth images with different grades in spot show that the texture homogeneity can reflect the concentration grade in real-time.