Copper ore, as an important non-renewable resource, has extremely high economic value. Copper is a metal widely used in many fields such as electrical, electronic, construction, and transportation. It is called the "mother of industry" because of its good electrical conductivity, thermal conductivity, ductility, and corrosion resistance.

The main problems faced by copper ore sorting include:

1.The ore composition is complex and contains a variety of minerals, such as iron, sulfur, silicon, etc. The presence of these minerals will affect the beneficiation process and increase the difficulty of beneficiation.

2.The ore particle size is uneven, and there is a mixture of fine and coarse particles, which will lead to unstable grinding and flotation effects.

3.The ore flotation effect is poor, and impurities such as iron and sulfur will have a negative impact on the flotation effect, resulting in a low copper recovery rate.

4.The reagent selection is difficult. Different copper ores require different reagents for flotation. It is not easy to correctly select the right reagent.

5.The problem of copper ore sliming. The ore slime formed by excessive crushing will affect the flotation effect and reduce the recovery rate of the concentrate.

6.The low grade of the concentrate may be caused by the low grade of the ore or the unreasonable beneficiation process.

In response to these problems, corresponding solutions can be adopted, such as the use of Mingder artificial intelligence ore sorting equipment.Before flotation, use artificial intelligence photoelectric mineral processing equipment to discard waste rock and remove harmful impurities (iron, sulfur). Improve the grade of copper ore entering flotation and improve the flotation effect ,save the cost of flotation in the later stage.

How does artificial intelligence photoelectric sorting equipment efficiently sort copper ore?

The raw copper ore is crushed, washed and screened to ensure that it is crushed to the appropriate particle size. The material enters the vibrating feeder and is evenly conveyed to the crawler belt to the sorting chamber. The photoelectric sensors and high-definition cameras in the sorting chamber scan the material to capture the material's multi-dimensional characteristics such as color, shape, size, texture, etc. The collected data is transmitted to the industrial computer, and the artificial intelligence algorithm analyzes the data to identify different types of materials. Based on deep learning and model recognition technology, the artificial intelligence system makes sorting decisions and determines the category of the material. According to the instructions of the artificial intelligence system, the mechanical sorting mechanism classifies and sorts the materials and separates different types of materials. The sorted materials are collected in different containers or conveyor belts, ready for the next step of processing or packaging.

Artificial intelligence photoelectric sorting technology can automatically extract the multi-dimensional characteristics of materials, such as texture, shape, color, glossy,luster etc., which greatly improves the sorting effect, expands the sorting scenarios and material types, meets the market's diversified and personalized sorting requirements, and solves the problem of limited color sorting materials in the current color sorter market.