基于图像特征的铜粗选过程病态工况识别

泡沫图像特征是指泡沫图像中与浮选性能相关的局部黑色水化区域大小,即局部光谱特征.针对这一局部光谱特征形状、大小无规则性,提出了一种基于多维主元分析的特征提取方法,并将提取的特征应用于铜浮选粗选过程病态工况识别.首先,描述了铜浮选粗选过程,分析了影响粗选过程的主要因素和黑色水化区域形成机理;然后,提出一种基于多维主元分析的图像局部光谱特征提取方法;最后,将基于多维主元分析的图像局部光谱特征提取算法应用于铜浮选粗选泡沫图像,并将所提取的图像特征用于铜粗选病态工况识别.工业现场数据验证了所提方法的有效性.

Sick Condition Recognition Based on the Image Feature of Froth Image in Copper Rough Process

The image features of copper flotation froth image means the size of the area of local black hydration in the froth image, which is called local spectral feature and related to flotation performance. A local spectral feature extraction method based on MPCA was proposed for the irregularity of the size and the shape, and the extracted features were used in copper rougher flotation process to identify sick conditions. Firstly, we described the copper rougher flotation process and analyzed the impact of the main factors roughing process and the formation mechanism of black hydration region. Then, a method was proposed to extract the local feature of image based on MPCA. Lastly, the image local feature extraction algorithm based on MPCA was applied to the copper flotation rougher froth image and the extracted image features were used in copper rougher process for sick condition recognition. The validity of the proposed method has been verified with industrial data.