For industrial flotation foam image processing, accurate bubble size measurement and feature extraction are very important to optimize the flotation process and to improve the recovery of mineral resources. This paper presents an improved algorithm to investigate mineral flotation foam image segmentation for mineral processing. Several libraries implemented for the Python programming language are used for image enhancement and compensation, quantitative analysis of factors influencing the image segmentation accuracy, and suggestions for improvement of the flotation foam image processing. The bubble characteristics-size and morphology-and the influence of the flotation conditions on the flotation foam image are analyzed. A Python implementation of the Retinex image compensation method-region-adaptive and multiscale-is proposed to address known issues of uneven illumination and shadows affecting flotation foam images, thereby improving brightness uniformity. Finally, an improved version of the watershed segmentation algorithm included in the Python Open Source Computer Vision library is used for segmentation analysis. The accuracy of the flotation foam image segmentation is 3.3% higher than for the standard watershed algorithm and the segmentation time is 9.9% shorter.

As a common depressant, acidified water glass (AWG) has strong inhibitory effects on fluorite and calcite. The inhibited fluorite is difficult to be recovered, thus resulting in the waste of resources and low flotation efficiency. In this study, the interaction of fluoride ions with fluorite and calcite surfaces was investigated, and its effects of AWG adsorption on mineral surfaces were evaluated. Micro-flotation experiments indicated that the flotation recovery of fluorite is 88.72% after fluoride ion treatment, that is, approximately fourfold with respect to that without fluoride ion modification. The results of solution chemical calculations showed that SiO(OH)₃⁻ is the main component to inhibit fluorite, and Si(OH)₄ is the main component to inhibit calcite in AWG solution. XPS and ICP-MS results showed that fluoride ions can improve the floatability of fluorite by converting CaSiO₃ on the surface of fluorite into CaF₂, but the conversion ability of Si(OH)₄ on the surface of calcite is weak, which increases the difference in floatability between fluorite and calcite. The above results were further verified by the analysis of flotation foam image and contact angle measurement. After fluorine ion treatment, the contact angle of fluorite increased, and it was more easily adsorbed on the foam. Therefore, the interaction of the fluoride ion with the fluorite surfaces eliminated the adsorption of AWG on fluorite, thereby resulting in the enhanced hydrophobicity of fluorite. Different from the traditional metal ions modification, the idea of anion modification in this paper is expected to be further studied.

Grinding is an important link in the process of mineral processing. It plays a vital role in mineral processing by optimizing the grinding process, improving the quality of grinding products and ensuring the follow-up operation indicators. In this paper, the Python language, intelligent theoretical control technology and mineral processing were combined to solve the problem of ore feeding control in mineral processing. Using error factor analysis, an extended control algorithm was designed. The NumPy library and data collected from the Yuan YangMou concentrator in China were used to quantitatively analyze the factors affecting the error of electronic belt scales. This paper introduces the use of Kalman filtering for electronic belt scale weight data to reduce the effect of noise and hence reduce errors. The factors affecting the process of mill feeding are also analyzed. The core ideas and methods of fuzzy control theory are summarized, and a Python-based fuzzy controller suitable for the mill feeding process that improves the overall robustness and accuracy of feeding system is implemented.