Intelligent sorting and cleaning processing method for paragenic ore of iron ore and fluorite

Abstract

The invention provides an intelligent sorting and cleaning processing method for iron ore and fluorite paragenic ore, which comprises the following steps: S1, crushing, grinding and the like are performed on the iron ore and fluorite paragenic ore, so that the granularity of the ore reaches a preset range; s2, the pretreated ore is sorted through intelligent sorting equipment, the intelligent sorting equipment recognizes the characteristic difference of iron ore and fluorite minerals through an image recognition technology or a sensor technology or a machine learning algorithm, and the iron ore and fluorite are separated; s3, the separated iron ore is subjected to magnetic separation, and the grade of the iron ore is further improved; s4, flotation is conducted on the separated fluorite, so that impurity minerals in the fluorite are removed, and the purity of the fluorite is improved; and S5, treating the sorted tailings, wherein the treatment comprises dehydration, drying and environment-friendly treatment. Through an intelligent separation technology, a refined process design, environment-friendly flow construction and data-driven optimization, efficient separation of iron ore and fluorite paragenic ore, comprehensive utilization of resources and clean production are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of ore processing, and in particular to a method for intelligent separation and clean processing of iron ore and fluorite paragenetic ore. Background Art

[0002] The treatment of co-existing iron ore and fluorite has always been a difficult point in the ore processing industry. Traditional sorting and processing methods have problems such as low efficiency, serious waste of resources, and unstable product quality. For example, during the sorting process, it is difficult to accurately identify the characteristic differences between iron ore and fluorite, resulting in poor separation effect; improper treatment of tailings during processing not only causes environmental pollution, but also fails to effectively recycle the useful components in the tailings. Therefore, an efficient, intelligent and environmentally friendly co-existing ore sorting and clean processing solution is urgently needed. Summary of the Invention

[0003] In view of this, the embodiments of the present invention hope to provide an intelligent separation and clean processing method for iron ore and fluorite paragenetic ore to solve or alleviate the technical problems existing in the prior art and at least provide a beneficial option.

[0004] The purpose of the present invention can be achieved by the following technical measures: a method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore, comprising the following steps:

[0005] S1. Crushing and grinding the iron ore and fluorite paragenetic ore to make the ore particle size reach the preset range;

[0006] S2. Sorting the pretreated ore using intelligent sorting equipment, wherein the intelligent sorting equipment uses image recognition technology, sensor technology, or machine learning algorithms to identify characteristic differences between iron ore and fluorite minerals and separate the iron ore from the fluorite;

[0007] S3, magnetic separation is performed on the separated iron ore to further improve the grade of the iron ore;

[0008] S4, flotation of the sorted fluorite to remove impurity minerals and improve the purity of the fluorite;

[0009] S5. Process the sorted tailings, including dehydration, drying and environmentally friendly disposal.

[0010] As a further preferred embodiment of the present technical solution: in the step S1, the preset range of the ore particle size is 0.074 mm to 2 mm, so as to ensure the efficient performance of the subsequent sorting operation.

[0011] As a further preferred embodiment of the present technical solution: in the step S2, the intelligent sorting equipment includes a high-resolution camera, a near-infrared spectral sensor and a deep learning algorithm, and the deep learning algorithm learns the spectral characteristics and morphological characteristics of iron ore and fluorite through a training data set to achieve high-precision mineral identification.

[0012] As a further preferred embodiment of the present technical solution: in the step S3, the magnetic separation adopts weak magnetic separation or strong magnetic separation, and the magnetic field strength is adjusted according to the magnetic properties of the iron ore.

[0013] As a further preferred embodiment of the present technical solution: in the step S4, oleic acid or sodium oleate is used as a collector for flotation, and the pH value of the pulp is adjusted to 8-10 to improve the flotation recovery rate of fluorite.

[0014] As a further preferred embodiment of the present technical solution: in the step S5, the tailings are dehydrated by a filter press, the moisture content of the dehydrated tailings is less than 15%, and the tailings are disposed of by environmentally friendly landfill or storage in a tailings pond.

[0015] As a further preferred embodiment of this technical solution: the method also includes real-time monitoring and data analysis of the entire processing process, collecting equipment operation data, mineral grade data and energy consumption data through the industrial Internet platform, and using big data analysis technology to optimize process parameters and improve production efficiency and resource utilization.

[0016] As a further preferred embodiment of the present technical solution: the method further includes conducting quality inspection on the sorted iron ore and fluorite, and determining the composition and grade of the minerals by using an X-ray fluorescence spectrometer or a chemical analysis method to ensure that the product quality meets national or industry standards.

[0017] As a further preferred embodiment of the present technical solution: an intelligent separation and cleaning processing equipment for iron ore and fluorite paragenetic ore, comprising the following components:

[0018] a. Crushing and grinding equipment, used for pre-processing of iron ore and fluorite symbiotic ore;

[0019] b. Intelligent sorting equipment for identifying and separating iron ore and fluorite;

[0020] c. Magnetic separation equipment, used for magnetic separation of the separated iron ore;

[0021] d. Flotation equipment, used to float the sorted fluorite;

[0022] e. Tailings treatment equipment, used for dehydration, drying and environmentally friendly disposal of tailings.

[0023] As a further preferred embodiment of the present technical solution: the equipment also includes a monitoring and data analysis system, which can monitor various parameters and equipment operating status during the processing in real time, and dynamically adjust and optimize the process parameters based on the collected data.

[0024] The embodiment of the present invention adopts the above technical solution, which has the following advantages:

[0025] 1. This invention relies on image recognition, near-infrared spectral sensing and deep learning algorithms to break through the limitations of traditional sorting and achieve high-precision identification of iron ore and fluorite; the industrial Internet and big data analysis are combined with the particle swarm optimization algorithm to promote sorting and processing from experience-driven to data-driven, accurately control the crushing and grinding particle size and magnetic separation and flotation parameters, and significantly improve the level of production intelligence and process flexibility.

[0026] 2. The present invention reduces the mineral misjudgment rate through intelligent sorting equipment, combines targeted optimization of magnetic separation and flotation processes, and greatly improves the magnetic iron recovery rate of iron ore and the recovery rate of fluorite concentrate; the tailings are dehydrated by filtration and valuable elements are re-selected to achieve "zero waste" of resources. At the same time, big data is used to establish a quantitative model of energy consumption and recovery rate, achieving both resource utilization and energy efficiency.

[0027] 3. The present invention adopts oleic acid-based environmentally friendly collectors through green production and circular economy construction to avoid pollution from traditional agents; tailings are landfilled or stored in accordance with strict environmental protection standards to strictly control the risk of heavy metal leakage; energy consumption is monitored in real time and parameters are optimized to practice the concept of green manufacturing; high-value elements in tailings are re-selected to form a circular chain of "resources-products-renewable resources".

[0028] 4. The present invention integrates the entire process equipment through equipment collaboration and efficiency upgrade to achieve closed-loop operation from raw ore to tailings disposal, reducing intermediate losses; the monitoring system and equipment are linked in real time to dynamically adjust process parameters; the equipment is highly adaptable and can adapt to the needs of different mining areas, and relies on the industrial Internet to support function iteration, reducing labor and debugging costs, ensuring production stability, and outputting high-quality mineral products that meet national standards, thereby enhancing market competitiveness.

[0029] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present invention will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 Flowchart of the method of the present invention. DETAILED DESCRIPTION

[0032] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0033] It should be clear that the following embodiments of the present disclosure are described through specific concrete examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure.

[0034] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0035] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The illustrations only show components related to the present disclosure and are not drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component can be changed at will, and the component layout type may also be more complicated.

[0036] Additionally, in the following description, specific details are provided to provide a thorough understanding of the examples. However, one skilled in the art will appreciate that the aspects described can be practiced without these specific details.

[0037] Figure 1 This is a flow chart of a method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to an embodiment of the present invention. It should be noted that if there are substantially the same results, the method of this application is not based on Figure 1 The process sequence shown is limited. Figure 1 As shown: A method for intelligent sorting and clean processing of iron ore and fluorite paragenetic ore, comprising the following steps: S1, crushing, grinding and other treatments on the iron ore and fluorite paragenetic ore to make the ore particle size reach a preset range; S2, using intelligent sorting equipment to sort the pretreated ore, the intelligent sorting equipment uses image recognition technology, sensor technology or machine learning algorithm to identify the characteristic differences between iron ore and fluorite minerals, and separate the iron ore from the fluorite; S3, magnetic separation of the sorted iron ore to further improve the grade of the iron ore; S4, flotation of the sorted fluorite to remove impurity minerals therein and improve the purity of the fluorite; S5, processing the sorted tailings, including dehydration, drying and environmentally friendly disposal.

[0038] Specifically, in step S1, the preset range of ore particle size is 0.074 mm to 2 mm to ensure efficient subsequent sorting operations.

[0039] Among them, the preset particle size range is: (0.074mm≤d≤2mm), and d is the particle size of the ore particles.

[0040] Key formula: Grinding efficiency calculation formula

[0041] Where: (η) is the grinding efficiency (%), (m1) is the mass of coarse-grained ore before grinding (t), (m2) is the mass of oversized ore after grinding (t), and the target grinding efficiency is (η≥90%).

[0042] Specifically, in step S2, the intelligent sorting equipment includes a high-resolution camera, a near-infrared spectral sensor and a deep learning algorithm. The deep learning algorithm learns the spectral characteristics and morphological characteristics of iron ore and fluorite through a training data set to achieve high-precision mineral identification.

[0043] Among them, high-resolution camera (pixel (≥5 million)), near-infrared spectral sensor (wavelength range (900-1700nm)).

[0044] The mineral identification model based on deep learning adopts the improved YOLOv5 algorithm, and the loss function is cross entropy loss:

[0045] =0), The model predicts probability and achieves recognition accuracy (≥95%) through training.

[0046] Specifically, in step S3, the magnetic separation adopts weak magnetic separation or strong magnetic separation, and the magnetic field strength is adjusted according to the magnetic properties of the iron ore.

[0047] Among them, weak magnetic separation: suitable for magnetite (specific magnetic susceptibility (κ>3000×10 -6 cm 3 / g), magnetic field strength (H = 100-200mT), target iron concentrate grade (TFe ≥ 65%); strong magnetic separation: suitable for weakly magnetic minerals such as hematite, magnetic field strength (H = 1-2T), magnetic iron recovery rate (≥ 95%).

[0048] Specifically, in step S4, oleic acid or sodium oleate is used as a collector in flotation, and the pH value of the pulp is adjusted to 8-10 to improve the flotation recovery rate of fluorite.

[0049] The collector is oleic acid or sodium oleate, with a dosage of (C = 300-500 g / t); the pH value of the pulp is adjusted to (8 ≤ pH ≤ 10) by lime or sodium carbonate;

[0050] The relationship between pH and collector adsorption capacity conforms to the Langmuir isotherm equation:

[0051]

[0052] Where: (Γ) is the adsorption capacity of the collector (mg / g), (Γ max ) is the saturated adsorption capacity, \(K\) is the adsorption equilibrium constant, and (C) is the collector concentration ((mol / L)).

[0053] Flotation index: fluorite concentrate (CaF2) purity (≥95%), recovery rate (≥85%).

[0054] Specifically, in step S5, the tailings are dehydrated using a filter press, and the moisture content of the dehydrated tailings is less than 15%, and the tailings are disposed of by environmentally friendly landfill or storage in a tailings pond.

[0055] More specifically, the tailings moisture content calculation formula is:

[0056] Where: (m 水 ) is the mass of water in the tailings (kg), (m { {Total}}) is the total mass of tailings (kg), target (w<15%).

[0057] Disposal method: When the content of valuable elements (>0.5%), enter the re-selection process; harmless tailings are landfilled in an environmentally friendly manner (liner permeability (≤10 -7 cm / s)) or tailings pond storage (in compliance with GB50863-2013).

[0058] Specifically, the method also includes real-time monitoring and data analysis of the entire processing process, collecting equipment operation data, mineral grade data and energy consumption data through the industrial Internet platform, and using big data analysis technology to optimize process parameters and improve production efficiency and resource utilization.

[0059] More specifically, a process parameter optimization model is established based on big data analysis, and the particle swarm optimization (PSO) algorithm is used to solve the optimal parameter combination. The objective function is:

[0060]

[0061] Where: (X) is the process parameter vector (such as grinding fineness, magnetic field strength), (Eelec) is the power consumption, (α, β, γ) are weight coefficients, (E ref ) is the reference power consumption, (η recovery ) is the resource recovery rate, (C XRF ) is the value detected by X-ray fluorescence spectrometer, (C std ) is the standard value of grade.

[0062] Specifically, the method also includes quality testing of the sorted iron ore and fluorite, using an X-ray fluorescence spectrometer or chemical analysis method to determine the composition and grade of the minerals to ensure that the product quality meets national or industry standards.

[0063] Specifically, an intelligent separation and cleaning processing equipment for iron ore and fluorite paragenetic ore includes the following components:

[0064] a. Crushing and grinding equipment, used for pre-processing of iron ore and fluorite symbiotic ore;

[0065] b. Intelligent sorting equipment for identifying and separating iron ore and fluorite;

[0066] c. Magnetic separation equipment, used for magnetic separation of the separated iron ore;

[0067] d. Flotation equipment, used to float the sorted fluorite;

[0068] e. Tailings treatment equipment, used for dehydration, drying and environmentally friendly disposal of tailings.

[0069] Specifically, the equipment also includes a monitoring and data analysis system that can monitor various parameters and equipment operating status during the processing in real time, and dynamically adjust and optimize process parameters based on the collected data.

[0070] In this embodiment, the specific present invention is in operation: first, the co-existing ore particle size is processed to 0.074mm-2mm by crushing and grinding equipment, and the grinding efficiency calculation formula is used to ensure the grinding effect; then, the intelligent sorting equipment uses a high-resolution camera, a near-infrared spectral sensor and a deep learning algorithm to identify differences based on spectral and morphological characteristics, and uses a cross-entropy loss function to train a model to achieve high-precision separation of iron ore and fluorite; then, the sorted iron ore is selected for weak magnetic separation or strong magnetic separation according to the magnetic strength to improve the grade, oleic acid or sodium oleate is used as a collector for fluorite, and the pH value of the slurry is adjusted to 8-10 for flotation purification; the tailings are dehydrated by a filter press to a moisture content of less than 15%, and re-selection, environmentally friendly landfill or tailings pond storage is selected according to the valuable element content; at the same time, real-time monitoring is carried out using the industrial Internet platform, process parameters are optimized based on big data analysis and particle swarm optimization algorithm, and quality inspection of the sorted products is carried out by X-ray fluorescence spectrometer or chemical analysis method. The entire set of equipment and methods work together to achieve efficient, intelligent sorting and clean processing.

[0071] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.

[0072] In the present disclosure, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0073] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0074] Various changes, substitutions, and modifications may be made to the technology described herein without departing from the teachings defined by the appended claims. Moreover, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of things, means, methods, and actions described above. Currently existing or later developed processes, machines, manufactures, compositions of things, means, methods, or actions that perform substantially the same function or achieve substantially the same results as the corresponding aspects described herein may be utilized. Accordingly, the appended claims include within their scope such processes, machines, manufactures, compositions of things, means, methods, or actions.

[0075] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0076] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore, characterized in that: The following steps are involved: S1. Crushing and grinding the iron ore and fluorite paragenetic ore to make the ore particle size reach the preset range; S2. Sorting the pretreated ore using intelligent sorting equipment, wherein the intelligent sorting equipment uses image recognition technology, sensor technology, or machine learning algorithms to identify characteristic differences between iron ore and fluorite minerals and separate the iron ore from the fluorite; S3, magnetic separation is performed on the separated iron ore to further improve the grade of the iron ore; S4, flotation of the sorted fluorite to remove impurity minerals and improve the purity of the fluorite; S5. Process the sorted tailings, including dehydration, drying and environmentally friendly disposal.

2. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: In the step S1, the preset range of the ore particle size is 0.074 mm to 2 mm to ensure the efficiency of the subsequent sorting operation.

3. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: In the S2 step, the intelligent sorting equipment includes a high-resolution camera, a near-infrared spectral sensor and a deep learning algorithm. The deep learning algorithm learns the spectral characteristics and morphological characteristics of iron ore and fluorite through a training data set to achieve high-precision mineral identification.

4. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: In the step S3, the magnetic separation adopts weak magnetic separation or strong magnetic separation, and the magnetic field strength is adjusted according to the magnetic properties of the iron ore.

5. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: In the step S4, oleic acid or sodium oleate is used as a collector for flotation, and the pH value of the pulp is adjusted to 8-10 to improve the flotation recovery rate of fluorite.

6. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: In the step S5, the tailings are dehydrated by a filter press, and the moisture content of the dehydrated tailings is less than 15%. The tailings are disposed of by environmentally friendly landfill or storage in a tailings pond.

7. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: The method also includes real-time monitoring and data analysis of the entire processing process, collecting equipment operation data, mineral grade data and energy consumption data through the industrial Internet platform, and using big data analysis technology to optimize process parameters and improve production efficiency and resource utilization.

8. The method for intelligent separation and cleaning of iron ore and fluorite paragenetic ore according to claim 1, characterized in that: The method also includes quality testing of the sorted iron ore and fluorite, using an X-ray fluorescence spectrometer or chemical analysis method to determine the composition and grade of the minerals to ensure that the product quality meets national or industry standards.

9. An intelligent separation and cleaning processing equipment for iron ore and fluorite paragenetic ore, characterized in that: Includes the following components: a) Crushing and grinding equipment, used for pre-processing iron ore and fluorite symbiotic ore; b) Intelligent sorting equipment for identifying and separating iron ore and fluorite; c) Magnetic separation equipment, used for magnetic separation of the separated iron ore; d) Flotation equipment, used for flotation of the sorted fluorite; (e) Tailings treatment equipment, used for dewatering, drying and environmentally friendly disposal of tailings.

10. The intelligent separation and cleaning processing equipment for iron ore and fluorite paragenetic ore according to claim 9, characterized in that: The equipment also includes a monitoring and data analysis system that can monitor various parameters and equipment operating status during the processing in real time, and dynamically adjust and optimize process parameters based on the collected data.

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