As a non-metallic ore resource,fluorite is widely used in various industries.With the increasing global demand for fluorite and the differentiation of resource quality, traditional sorting processes face bottlenecks such as low efficiency, high cost, and poor adaptability, making it difficult to meet the comprehensive demands of modern mining for efficiency, environmental protection, and value.

In recent years, the development of artificial intelligence beneficiation technology has provided opportunities for the calcium reduction treatment of high calcium fluorite ore, the extraction of low-grade ore, and the optimization of high-grade ore.

一、The significance of AI sorting tech for high calcium fluorite ore

For high calcium fluorite ore,Mingde Optoelectronics' AI sorting machine takes a different approach - its AI recognition 3.0 system uses multispectral scanning technology, combined with the existence of a certain degree of dissociation after the crushing of fluorite ore, to capture the subtle feature differences between high calcium and low calcium fluorite ores, and dynamically sorts fluorite particles through deep learning algorithms.

Experimental data shows that after pretreatment by Mingde equipment, the calcium carbonate content of some high calcium fluorite ores can be reduced from 15% -25% of the original ore to below 8%, increasing the recovery rate of calcium fluoride in the flotation section to over 85%, and stabilizing the concentrate grade at 92% CaF ₂ or above.

二、The significance of AI sorting tech for low-grade ore

When the grade of fluorite raw ore is between 20% and 30% of the economic threshold, the economic feasibility of direct flotation is often high and low, which is a headache for most mines. However, by using the Mingde AI ore sorting machine to revive low-grade fluorite, the dual objectives of "waste disposal enrichment" optimization can be achieved.

三、AI ore sorting machine amplifies the value of high-grade fluorite

Outer Mongolia has a large amount of high-quality fluorite, but due to the backward heavy medium sorting process in the area, the raw ore transported to China often contains 20% -30% amorphous fluorite.

The Mingde AI sorting machine innovatively adopts multispectral imaging technology to accurately identify the characteristic differences of different crystals and fluorite ores of different values in fluorite ore. Based on deep learning models and dynamic threshold algorithms, the system can complete ore feature analysis and sorting within 0.5 seconds.