The application scenarios of AI technology in mining resource sorting mainly include the following aspects: 1. Exploration of new minerals: AI technology has begun to be applied to the exploration of new minerals, such as using machine learning algorithms to analyze geological data and predict the best drilling locations. This technology has been successfully applied to gold exploration and is being used in the exploration of other minerals. 2. Unmanned mining vehicles: The application of AI technology in large mining companies is mainly to improve operational efficiency. Unmanned vehicles have been used in open-pit mines, and unmanned driving is achieved through automated transportation systems, which improves the efficiency and safety of mine operations. 3. Ore sorting optimization: AI technology can classify and identify ores through image recognition technology, improving sorting efficiency and accuracy. Data analysis and prediction models can predict the quality and composition of ores in advance, help adjust sorting parameters, and improve ore utilization. https://www.mdoresorting.com/mingde-ai-sorting-machine-separate-phosphorite-ore   4. Mineral association analysis: AI technology can predict the location and type of new mineral deposits through mineral association analysis. This method uses the combination of minerals formed under specific physical and chemical laws. For example, the formation of minerals is closely related to the chemical composition of the host rock and environmental conditions. 5. Mining resource exploration and mining: The application of AI technology in mining resource exploration and mining includes remote monitoring, automated mining, data analysis and decision support, intelligent safety monitoring, environmental monitoring, logistics management, data analysis, decision support, and automated control. These applications improve the efficiency, safety, and environmental protection of mining operations. 6. Mine management: AI technology can help mine managers analyze various production and operation data in a timely manner, provide visual data insights and intelligent decision-making support, and improve management efficiency. Automated and intelligent management AI technology can realize automated control of mining equipment and operating processes, improve operating efficiency and safety, and achieve more refined mine management. 7. Mine safety: AI technology can realize remote control and unmanned mine operations, improving the safety and work efficiency of operators. Advanced AI safety monitoring systems can analyze the mine operating environment in real time, promptly identify potential safety hazards, and warn operators, greatly improving mine safety. 8. Mine environmental monitoring: AI technology can monitor mine soil, water quality, air quality and other indicators in real time to detect environmental problems in a timely manner. Predictive analysis models can predict environmental change trends and provide a basis for formulating environmental protection measures. 9. Mining logistics: AI technology is revolutionizing mining logistics management. From automated loading and unloading to intelligent scheduling, unmanned transportation to real-time inventory monitoring, AI plays a key role in improving mining logistics efficiency, reducing costs, and enhancing safety. 10. Mine data analysis: AI technology can help mining companies quickly process and analyze massive amounts of production, environmental, safety and other data to uncover hidden value and patterns. Through AI technology, mining companies can better predict equipment failures, optimize production processes, improve resource utilization, and improve overall operational efficiency. 11. Mining decision support: AI technology can help mining companies make more intelligent and data-driven decisions. By analyzing massive production data, market forecasts, environmental monitoring and other information, AI systems can provide mine managers with more comprehensive decision-making suggestions and improve the operating efficiency and risk management capabilities of mines. 12. Mine automation: The application of AI technology in mine automation includes self-driving mining trucks, automated mining drilling, and intelligent ore sorting. These technologies improve production efficiency, reduce manual intervention, and improve operational safety. 13. Remote control of mines: AI technology can achieve real-time monitoring and automated control of mine sites through remote sensing, machine vision, machine learning and other technologies, greatly reducing the need for manual entry into dangerous environments. Remote control technology can also help mining companies improve the flexibility of production management and achieve effective management of distributed mines. These application scenarios demonstrate the wide application and huge potential of AI technology in mining resource sorting, indicating that mining will become more intelligent and efficient in the future.  

Gold deposits can be broadly classified into vein gold deposits and placer gold deposits. The vein gold deposits are mainly formed by internal geological forces, mainly by volcanoes, magma, and geological actions; the placer gold deposits are mainly formed by mountain gold deposits exposed on the surface, which are weathered, eroded, and broken into gold sand, gold grains, gold flakes, and gold foam after long-term weathering, erosion, and crushing. Under the action of wind and water flow, they are gathered and deposited in rivers, lakes, and coasts, forming alluvial, alluvial, or coastal placer gold deposits; another part is weathered and eroded to form residual placer gold deposits or slope-accumulated placer gold deposits. The mineralization age of this type of ore is generally relatively long. According to the associated conditions, my country's gold deposit types can also be divided into gold-bearing quartz veins, gold-bearing pyrite quartz veins, gold-bearing pyrite altered granites, gold-bearing polymetallic sulfide ore quartz veins, gold-bearing oxide ore quartz veins, and gold-bearing tungsten-arsenic ore quartz veins. The grade of vein gold ore in industrial mining is generally 3~5g/ton, with a cut-off grade of 1~2g/ton, and the grade of placer gold is 0.2~0.3g/m3, with a cut-off grade of 0.05~0.1g/m3. However, the current gold mining in my country is mainly based on vein gold deposits, accounting for about 75%~85%. At present, gold mines are widely used in jewelry, industry, high-tech and other industries. Due to its scarcity and non-renewable nature, its overall value is relatively high. At present, the gold ore dressing methods are mainly divided into four types: gravity separation, flotation, chemical separation, and photoelectric separation. Gravity separation is suitable for coarse gold recovery. It is generally an auxiliary process in gold ore dressing and is used as a pre-selection process before flotation or chemical separation. Flotation is widely used in rock deposits. There are suction or aeration stirring flotation machines for flotation. Chemical separation mainly includes amalgamation and chlorination. Amalgamation is mainly suitable for coarse monomer gold, but it is gradually replaced due to its high pollution. Chlorination mainly includes stirring chlorination and percolation chlorination. The above three separations are conventional gold ore separations. For gold mines with economic mining grade or higher than industrial grade, the separation cost is lower than the economic cost. However, the general situation of gold mines in my country is that there are fewer rich mines and more poor mines. In terms of mining difficulty, there are fewer easy mines and more difficult mines. Most gold mines have a grade of less than 2 grams/ton, which is at or below the critical mining grade. If the above methods are used for direct separation, many gold mines will be lower than the economic mining value. The photoelectric sorting method grasps the pain points and difficulties of domestic gold ore sorting, and uses AI + photoelectric sorting to enrich the gold ore by pre-discarding the gold ore, thereby achieving a higher economic mining grade, and solving the problem of low grade and high sorting cost of domestic gold ore. The working principle is mainly to crush and dissociate the gold ore, and then use the AI sorting machine to establish a multi-dimensional three-dimensional model of the ore. The AI photoelectric sorting machine is used to identify the comprehensive characteristics of the gold ore surface, such as texture, color, gloss, shape, and reflectivity. After the industrial computer is combined with AI technology, the concentrate and waste rock in the gold ore are sorted out, so as to achieve the purpose of gold ore enrichment.   The ore that has passed the AI ore sorting machine only needs normal crushing and dissociation, and the particle size is 0.5cm-10cm, which is about 3-4 times the size of the selected particle size. It can be directly sorted and enriched, and the discarded tailings can be used as materials for various buildings, mine backfill, etc. After enrichment, the gold ore is separated by flotation or chemical separation. Pre-disposal reduces the processing level of the original ore and saves the processing cost of subsequent processes. For some gold mines below the economic mining grade, AI ore sorting machines can be used to enrich them to the economic mining grade, thereby increasing the utilization value of a large number of low-grade gold mines. AI sorting machines can not only sort gold ore, but also can use AI machines to sort gold associated ores as long as they can be crushed and dissociated, thereby increasing the comprehensive utilization rate of the mine. At the same time, the cost of the AI sorting machine itself Mingde Optoelectronics AI Ore Sorting Machine has mature technical accumulation for gold ore sorting. It can pre-dispose waste tailings on the premise of enriching gold ore, and the gold grade of the discarded tailings is far lower than the economic mining grade.

As we all know, mineral resources are the pillar of national infrastructure. During the mining process, most ores exist in the state of mineral and gangue coexistence. Only after a series of processing procedures can usable minerals be obtained. Before the ore can be effectively used, it needs to be crushed and dissociated, and then enriched by the corresponding mineral processing method. The so-called dissociation degree of a certain mineral is the ratio of the number of particles of the mineral monomer dissociated to the sum of the number of intergrowth particles containing the mineral and the number of particles of the mineral monomer dissociated. First, the block ore particles change from large to small, and various useful minerals are dissociated by reducing the particle size. First, in the crushing process, some of the various minerals that were originally intergrowthed together crack along the mineral interface and become particles containing only one mineral, which we call monomer dissociated particles, but there are still some small mineral particles that contain several minerals intergrowthed together, which are called intergrowth particles. Over-crushing mainly refers to the use of excessive grinding to achieve the full dissociation of useful minerals. In this process, more fine particles that are difficult to select are produced, that is, the phenomenon of "over-crushing" occurs. Over-crushing not only affects the grade and recovery rate of the concentrate during the selection process, but also increases the consumption of the grinding and selection process due to unnecessary crushing, resulting in increased beneficiation costs. The main hazards of over-crushing are: an increase in useful fine particles that are difficult to recover, low concentrate grade and recovery rate, increased machine loss, reduced unit time capacity, and increased useless power consumption of crushed ore. From the perspective of mineral structure, except for a few extremely coarse-grained ores that can obtain a considerable number of monomer dissociated particles after crushing, most ores must be ground to obtain a relatively high degree of dissociation. Ore crushing and grinding are too coarse and the degree of dissociation is insufficient, and too fine will cause equipment wear and increased consumption. Too coarse or too fine will lead to low concentrate grade and recovery rate. Therefore, appropriate grinding fineness is a necessary condition for achieving good separation of useful minerals and gangue minerals. Mineral processing workers should pay attention to the selection of crushing processes and equipment, strictly control the operating conditions, and strictly control the grinding fine powder within the optimal range determined by the mineral processing test. After some ores are crushed, there will be a certain proportion of low-economic-grade tailings or waste rocks with good dissociation. If such ores enter the subsequent grinding, it will directly affect the concentrate recovery and power consumption cost. Some concentrators adopt the method of early disposal and early selection to discard these useless tailings, which can not only release the production capacity of the concentrator, but also reduce the discharge of tailings after fine grinding, reduce solid mineral waste, and extend the service life of the tailings pond. As a company specializing in the research and development and production of ore sorting equipment, the photoelectric mineral processing products launched by MINGDE Optoelectronics are mainly used in the pre-sorting and pre-discarding of lump ores. According to the different degrees of dissociation of the ore, it can be used for ore sorting within the range of 0.3-15cm; it is suitable for sorting ores with different characteristics such as color, texture, texture, shape, gloss, shape, density, etc. The types of ores currently used by the equipment include fluorite, talc, wollastonite, calcium carbonate, gold mine, brucite, magnesite, silicon slag, pebbles, silica, phosphate rock, coal gangue, sponge titanium, monocrystalline silicon, lithium mica, spodumene, barite, pegmatite, tungsten tailings, coal-based kaolin and other minerals. MINGDE Optoelectronics can provide professional sorting equipment and solutions for ore sorting problems!