Geological mineral mining, sorting and sampling device based on machine learning

Abstract

The invention relates to the technical field of mineral mining, in particular to a geological mineral mining, sorting and sampling device based on machine learning. The geological mineral mining, sorting and sampling device comprises a shell, a feeding mechanism is arranged on the shell, a primary screening mechanism and a filtering mechanism are arranged in the shell, dredging mechanisms are arranged on the shell and the filtering mechanism, a discharging mechanism is arranged on the shell, and a sampling mechanism is arranged in the discharging mechanism. The primary screening mechanism is arranged inside the shell, so that the primary screening mechanism can play a role in screening mineral raw materials at the beginning of sorting and mining, impurities with too large particles are removed, it is guaranteed that the sorted raw material particles are roughly the same, influences on subsequent processing steps are avoided, the filtering mechanism is arranged inside the shell, so that the screening and filtering particle size of the mineral raw materials can be conveniently and properly adjusted, different mining and processing requirements are met, the dredging mechanisms are arranged on the shell and the filtering mechanism so that the filtering mechanism can be dredged conveniently in the operation process, and blockage of the filtering mechanism is avoided.

Description

technical field [0001] The invention relates to the technical field of mineral mining, in particular to a sorting and sampling device for geological mineral mining based on machine learning. Background technique [0002] The development of the mining industry has greatly promoted the process of urbanization, employment of labor force and social stability. Mineral resource mining refers to the mining of solid metal and non-metallic deposits, including surface ore body outcrops and open-pit mining of shallow ore bodies, blind mines, and underground mining of deep ore bodies. With the continuous advancement of mining technology, some intelligent mining equipment based on machine learning has gradually begun to appear. [0003] However, in the actual mining process, due to the fact that most of the mineral raw stones are irregular in shape and have different sizes and volumes, in order to succeed in the subsequent mining and processing, it is necessary to ensure that the partic...

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Problems solved by technology

[0003] However, in the actual mining process, due to the fact that most of the mineral raw stones are irregular in shape and have different sizes and volumes, in order to succeed in the subsequent mining and processing, it is necessary to ensure that the particle size of the ore is basically the same, especially for some loose textures such as talc. For the minerals, if there are some hard and large-grained impurities mixed in it, it will have a great impact on the subsequent processing steps; in the actual screening process, most of the traditional screening components are fixed inside the equipment Yes, but sometimes according to different processing requirements, different sieving particle sizes may be required, and at the same time, during the long-term sieving process, the filter screen may also be clogged; in addition, in the primary stage of mining and sorting, If the sorted minerals are directly sent to the next processing step, if there are some defects in the sorted minerals such as particle size and quality, it will adversely affect the subsequent production and processing

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