In recent years, the development of gold resources has gradually transformed to low-grade, complex symbiotic ores, and traditional mineral processing technology faces problems such as high cost, low efficiency, and waste of resources. As a leading company in the field of intelligent sorting, MINGDER has launched a new generation of intelligent mineral processing equipment system based on its independently developed spectral recognition technology and artificial intelligence algorithm, opening up an innovative path for gold mining companies to "improve quality and efficiency, and green development". Its ore color sorter and AI intelligent sorter have achieved technological breakthroughs in multiple projects in Henan, Fujian, Jiangxi, Shandong and other places, promoting the development and utilization of gold resources to a new height.

Case 1: Application practice of ore color sorter in a vein quartz gold mine in Henan

In a vein quartz gold mine in Henan, quartz is the main mineral (content 60%-90%), and gold is mostly fine particles wrapped in quartz or pyrite, arsenopyrite and other sulfides, with fine embedded particles (often needing to be ground to -200 mesh), resulting in traditional sorting processes relying on full-grade grinding and flotation, which is costly. The high hardness of quartz causes grinding power consumption of 30-50kWh/ton, and the equipment wear is significant. In the flotation process, a large amount of inhibitors need to be added to control the floating of quartz, which further increases the cost of reagents. In addition, fine-grained quartz causes the viscosity of the ore pulp to increase, the gold recovery rate is reduced by 5%-10%, and the tailings account for 70%-80% of the original ore, and the processing cost is 15-20 yuan/ton. In response to the above problems, a mining company uses MINGDER AI sorter pre-selection technology to systematically optimize the process. Based on the color difference between quartz and sulfide (off-white quartz and yellow-brown sulfide), after coarse crushing (particle size 10-50mm), AI optical recognition and sorting are used to remove 40%-60% of pure quartz without gold, which is directly sold as quartz sand. After pre-selection, the ore sulfide is enriched, the grinding amount is reduced by more than 50%, the power consumption per ton of ore is reduced by 50%, the amount of flotation reagents is reduced by 50%, and the gold recovery rate is increased by 3%-5%. The tailings volume was reduced to 40%-60%, the processing cost was reduced by 40%-50%, and the sorting of quartz could generate an additional 200-500 yuan/ton.

After the project was implemented, the grade of the raw ore jumped from 1.5g/t to 3.2g/t, and the annual processing volume increased by 180,000 tons. The waste quartz sand produced by sorting is sold as high-quality building materials, with an annual revenue of more than 18 million yuan, truly realizing the "full use" of resources. The person in charge of the mining area said: "This system not only solves the problem of low-grade ore storage, but also transforms tailings into a new economic growth point, providing a new idea for the sustainable development of mines."

Case 2: AI intelligent sorting machine breakthrough in Jiangxi pyrite associated gold mine

A large pyrite gold mine in Jiangxi has problems such as complex mineral symbiosis, low grade, high reagent consumption in traditional flotation process, and difficulty in separating sulfur and gold. MINGDER AI sorting machine realizes efficient pre-selection and discarding of ore through multimodal sensing and deep learning algorithms. Based on the close symbiosis of gold and sulfides (pyrite, pyrrhotite, etc.), this technology uses multi-dimensional data fusion analysis such as hyperspectral recognition and high-resolution imaging to accurately identify the physical and chemical differences between gold-bearing pyrite and gangue minerals.

During the sorting process, the ore enters the intelligent sorting system after crushing and screening. The surface characteristics of the minerals are analyzed in real time through dynamic modeling. Combined with the occurrence law of gold elements in pyrite minerals, a "gold-sulfur" correlation criterion model is established, which can effectively distinguish high-value ore blocks from low-grade waste rocks. Industrial tests have shown that the pre-selection discard rate of pyrite-associated gold ore by this equipment is 25%-40%, and the waste gold loss rate is controlled below 0.1g/t, which significantly reduces the subsequent grinding and flotation process processing volume and reagent consumption.

The promotion of this technology provides a new idea for the development of complex associated gold mines. Through front-end pre-selection, intensive resource utilization is achieved. While improving the economic benefits of mineral processing, tailings emissions and energy consumption are reduced, which meets the needs of green mine construction.

Project operation data shows that the system's early discard rate reaches 35%, the gold grade of the selected ore increases by 1.5 times, and the gold content of the sulfur concentrate drops to below 0.1g/t. Compared with the traditional process, it saves 4.2 million yuan in reagent costs each year, reduces tailings emissions by 60,000 tons, and reduces unit energy consumption of the selected ore by 35%, truly realizing "green gold extraction".

Technological innovation leads industry change

MINGDER continues to lead the industry with two core technological advantages:

1. Spectral big data platform: Build a mineral feature database covering 500+ mines worldwide, and quickly adapt to new mineral species through transfer learning technology

2. Intelligent decision-making engine: Develop a system with self-optimization capabilities, and shorten the response time of dynamic adjustment of sorting parameters to 50ms

At present, its equipment has been implemented in more than 200 projects in 15 countries, helping customers to improve resource utilization by 42% on average and reduce mineral processing costs by 35%. As a person in charge of a mining company in Yunnan said: "AI sorting machines not only bring economic benefits, but also promote us to establish a digital mine management system, which is a value that traditional equipment cannot achieve."

As the "dual carbon" strategy is further promoted, in the future, intelligent sorting technology will surely reshape the gold industry landscape.