As an important strategic mineral resource, fluorite is widely used in metallurgy, chemical industry, optics and other fields. With the growth of global demand for fluorite and the differentiation of resource quality, traditional sorting processes face bottlenecks such as low efficiency, high cost and poor adaptability, and it is difficult to meet the comprehensive demands of modern mining for efficiency, environmental protection and value. In recent years, with the development of artificial intelligence technology, especially the continuous innovation of technology in the field of ore sorting, the combination of multi-spectral recognition, deep learning algorithm and high-speed execution system has provided innovative solutions for the fine sorting of fluorite ore, especially in the fields of calcium reduction treatment of high-calcium fluorite ore, low-grade ore improvement and high-grade ore optimization.

Breakthrough of high-calcium fluorite ore: precise separation under multi-spectral recognition technology

As the main fluorite production area in China, Inner Mongolia has always had the "pain of high calcium" in fluorite ore, which is essentially the contradiction of smelting caused by the symbiosis of calcium carbonate and calcium fluoride crystals. The traditional flotation process requires acid leaching to adjust the pH value to inhibit the floating of calcium carbonate, but it has defects such as high reagent consumption, fluctuations in calcium fluoride recovery rate (usually only 65%-75%) and high tailings treatment costs.

However, MINGDER Optoelectronics AI sorting machine takes a different approach - its artificial intelligence recognition 3.0 system uses multi-spectral scanning technology and combines the fact that fluorite ore has a certain degree of dissociation after crushing to capture the subtle characteristic differences between high-calcium and low-calcium fluorite ores, and dynamically sorts fluorite particles through deep learning algorithms. Experimental data show that after pretreatment by MINGDER equipment, the calcium carbonate content of some high-calcium fluorite ores can be reduced from 15%-25% of the original ore to below 8%, so that the calcium fluoride recovery rate in the flotation stage can be increased to more than 85%, and the concentrate grade is stabilized at more than 92% CaF₂.

High-calcium fluorite mining area: Construct "AI roughing-flotation combined process", pre-process 10-50mm particle size ore by the sorter, and reduce the interference of calcium carbonate in the flotation stage;

Improvement of economic efficiency of low-grade ore: pre-sorting, discarding and resource utilization

When the grade of fluorite ore is between the economic critical line of 20%-30%, the economic efficiency of direct flotation is often high in cost and low in profit, which is a headache for most mines. However, by constructing an ore value model and realizing the dual-objective optimization of "discarding-enrichment", these "marginal resources" have been reborn. The equipment establishes a waste rock recognition model based on surface texture features, and removes siliceous rock, clay minerals and other gangue at high speed. Its intelligent gradient sorting mode - dynamically adjusts the sorting threshold through deep learning, so that the grade of the floating ore is increased to 35%-50%, the consumption of flotation reagents is reduced by 40%, and the flotation tailings are reduced by 30-45%. At the same time, the pre-discarded tailings are transferred to the building materials processing chain to form a "ore dressing-building materials" collaborative production model.

Low-grade mining area: adopt the "ladder sorting" mode, the first stage removes waste rocks with less than 8% CaF₂, and the second stage re-enriches 10%-30% CaF₂ores, forming a three-level resource system of floatable raw materials (>25%), building materials (8%-15%), and backfill (<8%).

Maximizing the value of high-grade ore: the ultimate release of value

The fluorite deposits in South Gobi Province, Outer Mongolia, contain a large number of crystal clear cubic fluorite crystals. Although the fluorite ore is of high grade (CaF₂＞65%) and complete crystallization, it is limited by the backward local heavy medium sorting process, and the raw ore transported to China is often mixed with 20%-30% amorphous fluorite. MINGDER sorting machine innovatively adopts multi-spectral imaging technology to accurately identify the characteristic differences of different crystals and different value fluorite ores in fluorite ore. According to the deep learning model and dynamic threshold algorithm, the system can complete ore feature analysis and sorting within 0.5s. Compared with the traditional process, it is improved by 300% and energy consumption is reduced by 75%. The transportation cost of every 10,000 tons of ore is saved by 450,000 US dollars. At the same time, due to the efficient sorting of the purple fluorite premium, the annual revenue of a single production line can reach tens of millions. The purity of the CaF₂ concentrate after sorting is stable at more than 95%, which greatly reduces the downstream smelting cost.

High-grade mining areas: deploy photoelectric intelligent sorting to complete high-grade pre-enrichment at the mining site, reduce cross-border transportation by 40%, and avoid ineffective transportation of inefficient ores;

Technical and economic analysis

Compared with traditional processes, AI sorting can shorten the investment recovery period of fluorite projects by 2-3 years:

Energy consumption: unit processing power consumption is 0.8-1.2 kWh/t, which is 70% lower than flotation

Labor cost: automation rate>95%, reducing the labor of the beneficiation plant by 30%

Environmental benefits: tailings pond capacity demand is reduced by 50%, and the risk of heavy metal pollution is reduced

Artificial intelligence sorting technology is reshaping the processing method of fluorite. From the precise dissociation of high-calcium ores to the economic development of low-grade ores, and then to the value-added utilization of high-grade fluorite, this technology promotes the industry's transformation to green and intelligent through the full optimization of the ore value chain, from resource consumption to value creation, and creates an industry of "precise sorting-low-carbon production-value transition" for fluorite mines.